1726 Mlflow Jobs - Page 35

Overview We are PepsiCo PepsiCo is one of the world's leading food and beverage companies with more than $79 Billion in Net Revenue and a global portfolio of diverse and beloved brands. We have a complementary food and beverage portfolio that includes 22 brands that each generate more than $1 Billion in annual retail sales. PepsiCo's products are sold in more than 200 countries and territories around the world. PepsiCo's strength is its people. We are over 250,000 game changers, mountain movers and history makers, located around the world, and united by a shared set of values and goals. We believe that acting ethically and responsibly is not only the right thing to do, but also the right thing to do for our business. At PepsiCo, we aim to deliver top-tier financial performance over the long term by integrating sustainability into our business strategy, leaving a positive imprint on society and the environment. We call this Winning with Pep+ Positive . For more information on PepsiCo and the opportunities it holds, visit www.pepsico.com. PepsiCo Data Analytics & AI Overview: With data deeply embedded in our DNA, PepsiCo Data, Analytics and AI (DA&AI) transforms data into consumer delight. We build and organize business-ready data that allows PepsiCo’s leaders to solve their problems with the highest degree of confidence. Our platform of data products and services ensures data is activated at scale. This enables new revenue streams, deeper partner relationships, new consumer experiences, and innovation across the enterprise. The Data Science Pillar in DA&AI will be the organization where Data Scientist and ML Engineers report to in the broader D+A Organization. Also DS will lead, facilitate and collaborate on the larger DS community in PepsiCo. DS will provide the talent for the development and support of DS component and its life cycle within DA&AI Products. And will support “pre-engagement” activities as requested and validated by the prioritization framework of DA&AI. Data Scientist-Gurugram and Hyderabad The role will work in developing Machine Learning (ML) and Artificial Intelligence (AI) projects. Specific scope of this role is to develop ML solution in support of ML/AI projects using big analytics toolsets in a CI/CD environment. Analytics toolsets may include DS tools/Spark/Databricks, and other technologies offered by Microsoft Azure or open-source toolsets. This role will also help automate the end-to-end cycle with Machine Learning Services and Pipelines. Responsibilities Delivery of key Advanced Analytics/Data Science projects within time and budget, particularly around DevOps/MLOps and Machine Learning models in scope Collaborate with data engineers and ML engineers to understand data and models and leverage various advanced analytics capabilities Ensure on time and on budget delivery which satisfies project requirements, while adhering to enterprise architecture standards Use big data technologies to help process data and build scaled data pipelines (batch to real time) Automate the end-to-end ML lifecycle with Azure Machine Learning and Azure/AWS/GCP Pipelines. Setup cloud alerts, monitors, dashboards, and logging and troubleshoot machine learning infrastructure Automate ML models deployments Qualifications Minimum 3years of hands-on work experience in data science / Machine learning Minimum 3year of SQL experience Experience in DevOps and Machine Learning (ML) with hands-on experience with one or more cloud service providers. BE/BS in Computer Science, Math, Physics, or other technical fields. Data Science - Hands on experience and strong knowledge of building machine learning models - supervised and unsupervised models Programming Skills - Hands-on experience in statistical programming languages like Python and database query languages like SQL Statistics - Good applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators Any Cloud - Experience in Databricks and ADF is desirable Familiarity with Spark, Hive, Pig is an added advantage Model deployment experience will be a plus Experience with version control systems like GitHub and CI/CD tools Experience in Exploratory data Analysis Knowledge of ML Ops / DevOps and deploying ML models is required Experience using MLFlow, Kubeflow etc. will be preferred Experience executing and contributing to ML OPS automation infrastructure is good to have Exceptional analytical and problem-solving skills

This role is for one of Weekday's clients Salary range: Rs 1000000 - Rs 2000000 (ie INR 10-20 LPA) Min Experience: 7 years Location: Bengaluru JobType: full-time Requirements About the Role: We are seeking a Lead Data Scientist with deep expertise in Natural Language Processing (NLP) and Large Language Models (LLMs) to drive advanced AI solutions and lead a team of data scientists and ML engineers. This is a unique opportunity to work on cutting-edge machine learning projects, influence product direction, and shape the company's data strategy. The ideal candidate is both a strategic thinker and a hands-on practitioner with strong experience in Python , end-to-end ML development, and leading teams. As a Lead Data Scientist, you will work closely with cross-functional teams including engineering, product, and business stakeholders to develop intelligent systems that create significant business impact. Key Responsibilities: Lead and mentor a team of data scientists to develop and deploy ML models, particularly in NLP, generative AI, and LLMs (e.g., GPT, BERT, LLaMA). Design, build, and implement end-to-end machine learning pipelines, from data preprocessing to production deployment. Collaborate with product and engineering teams to identify and scope machine learning opportunities aligned with business goals. Apply advanced NLP techniques (entity recognition, sentiment analysis, text summarization, etc.) to extract insights from unstructured data sources. Evaluate, fine-tune, and deploy large-scale language models for real-world applications such as chatbots, recommendation engines, document understanding, and automated decision systems. Drive innovation in data science methodologies and stay up to date with recent advancements in LLMs and generative AI. Conduct code reviews, set best practices for experimentation and model evaluation, and ensure model reproducibility and interpretability. Contribute to architectural decisions around model serving, feature engineering, and infrastructure. Communicate technical findings clearly to both technical and non-technical audiences. Required Skills & Qualifications: 7+ years of hands-on experience in data science, with at least 3 years in a leadership or technical mentorship role. Expertise in Python and its data/ML ecosystem (NumPy, pandas, scikit-learn, TensorFlow, PyTorch, etc.). Proven experience in Natural Language Processing, including practical use of transformers, LLMs, and fine-tuning of pre-trained models. Strong grasp of ML theory and statistical modeling. Experience building and deploying machine learning models in production environments. Ability to lead projects from ideation to delivery in fast-paced, collaborative environments. Strong communication and stakeholder management skills. Bachelor's/Master's/PhD in Computer Science, Data Science, Statistics, or related field. Nice to Have: Experience with vector databases (e.g., Pinecone, FAISS), RAG pipelines, and prompt engineering. Familiarity with cloud platforms (AWS, GCP, Azure) and MLOps tools (MLflow, Kubeflow, etc.). Publications or contributions to open-source projects in ML or NLP.

About Mihira Visual Labs Mihira Visual Labs is a research-driven CGI and VFX studio redefining filmmaking through AI- and ML-powered workflows. We specialize in the development and production of full-length animated films, empowering creators with cutting-edge tools to accelerate high-quality storytelling and IP creation. Our mission is to make world-class storytelling faster, more efficient, and more cost-effective — where human imagination is the only true differentiator. Role Overview The Lead AI/ML Engineer will spearhead the development and integration of artificial intelligence and machine learning solutions into our VFX production pipeline. You’ll work closely with pipeline developers, production managers, and creative teams to reimagine workflows, automate repetitive tasks, and push the boundaries of innovation in photorealistic rendering, stylized animation, and other CGI processes. This role combines deep technical expertise with a strong understanding of the demands of a fast-paced VFX/animation studio. Key Responsibilities AI Strategy & Roadmap Develop and maintain a strategic plan for implementing AI/ML across the VFX pipeline—covering data wrangling, rendering, asset management, animation, and post-production. Identify new approaches to innovate current workflows to increase efficiency and cut down on time. Algorithm & Model Development Research, design, and implement ML models (e.g., computer vision, generative models, style transfer) that improve artist efficiency, production speed, enhance image quality, or enable new creative possibilities. Optimize models for performance on local GPU/CPU clusters or cloud-based infrastructures. Pipeline Integration & Automation Collaborate with pipeline engineers to seamlessly integrate AI agents or tools into existing software stacks (e.g., Maya, Houdini, Nuke), ensuring minimal disruption to artists’ workflows. Develop automated solutions for tasks like rotoscoping, clean-up, crowd simulation, environment generation, or facial capture/animation. Infrastructure & Tooling Architect and maintain robust data pipelines, ensuring the secure collection and organization of high-quality datasets for training AI models. Evaluate and deploy containerization/MLOps tools (Docker, Kubernetes, MLflow, etc.) for scalable model training, inference, and monitoring. Performance Optimization Profile model performance, memory usage, and render times; implement optimizations in frameworks such as TensorFlow, PyTorch, or custom GPU pipelines. Work with DevOps/IT teams to configure and manage dedicated GPU farms or cloud compute resources. Research & Development Stay updated with state-of-the-art ML/DL techniques, particularly in generative AI, computer vision, and real-time rendering. Introduce emerging methods (e.g., stable diffusion, large language models, neural rendering) to innovate new production techniques. Mentorship & Collaboration Lead a small team of AI engineers or data scientists, providing guidance on best practices, code reviews, and architectural decisions. Educate and train production staff on AI-driven tools and workflows, fostering a culture of continuous improvement. Documentation & Reporting Create clear technical documentation for AI solutions, ensuring maintainability and scalability. Present progress, insights, and ROI to executive leadership, project stakeholders, and cross-functional teams. Qualifications & Skills Bachelor’s or Master’s degree in Computer Science, AI/ML, or related field. A PhD is a bonus but not mandatory. 5+ years of professional experience in applied machine learning or data science, with at least 2 years in a lead/managerial role. Previous experience in VFX, animation, gaming, or related entertainment industries is a bonus. Programming: Expert-level Python (C++ is a plus). ML Frameworks: Deep understanding of TensorFlow, PyTorch, scikit-learn, or similar libraries. Computer Vision & Generative Models: Familiarity with CNNs, GANs, autoencoders, stable diffusion, or neural radiance fields. Pipeline Tools: Experience with integration in VFX software (Maya, Houdini, Nuke) and plugin APIs.[Optional] DevOps & MLOps: Comfortable with containerization (Docker), orchestration (Kubernetes), CI/CD, and cloud platforms (AWS, Azure, GCP). Proven track record of translating production challenges into AI/ML solutions that deliver measurable efficiency gains or cost savings. Experience with model optimization (quantization, pruning) and GPU/CPU performance tuning. Collaboration: Excellent communication to bridge technical and creative teams, explaining complex concepts in clear, accessible language. Leadership: Ability to mentor junior engineers and foster a culture of experimentation and continuous learning. Agility: Adapts quickly to evolving project needs, production pipelines, and new AI techniques. A genuine interest in cinema, animation, or gaming—a plus if you have prior knowledge of the Baahubali IP or similar large-scale IPs. Creativity in applying AI to artistic challenges, from photorealistic digital humans to stylized animated sequences.

Are you excited by the challenge of building intelligent systems that live at the edge, understand natural language, and adapt to their environment? Do you thrive at the intersection of AI, embedded systems, and real-world impact? About Us – Mantra Softech Mantra Softech is a technology leader in biometric (Face, Finger, & Iris) solutions, now building the next generation of AI-powered smart home devices . As we expand into intelligent IoT, we're forming a world-class AI team to bring real-time perception, decision-making, and automation to the edge. Join us to shape the future of connected living. Role Overview We're looking for a Senior AI Engineer who thrives at the intersection of AI, embedded systems, and real-world impact. You will lead initiatives in LLMs, Edge AI, sensor fusion, ML Models and natural language interfaces to build AI-powered experiences across a new class of smart home devices. Location 📍 Ahmedabad, (Full-Time | On-Site) About the Role We are developing the next generation of intelligent systems that combine embedded sensing, AI at the edge, predictive maintenance, and natural language interfaces. If you're excited about deploying ML pipelines in real-world hardware, turning unstructured prompts into actions or queries, and working across the spectrum of edge devices, cloud infrastructure, and AI modeling — we want to work with you. Key Responsibilities Drive research initiatives and proof-of-concepts that push the state of the art in Gen AI and large-scale machine learning for home-automation projects Build AI agents capable of interpreting multi-modal inputs (vision, voice, sensors) and performing intelligent actions Design and deploy AI/ML pipelines across edge and cloud environments Develop natural language interfaces for voice and text-based interactions Work on prompt engineering and iteratively develop LLM-based solutions tailored to custom use cases like text-to-SQL, text-to-command, and context-aware queries Optimize ML models for embedded deployment and real-time execution Prototype novel generative AI solutions, integrate advancements into production, and collaborate with research partners. Integrate real-time streaming data (video/audio/sensor) into analytics pipelines and AI workflows Implement MLOPs workflows : model versioning, retraining, monitoring Collaborate on cloud infrastructure (AWS/Azure/GCP) for scalable backend and edge-cloud sync. Required Skills 3–5 years of hands-on experience in AI/ML system development Expertise in Python (and/or C/C++), PyTorch/TensorFlow, and ML frameworks Solid foundation and expertise in developing and deploying statistical ML models Experience with ML frameworks like Scikit-learn, PyTorch, TensorFlow,OpenCV etc. Hands-on experience with real-life signal/data processing (audio, sensor data, etc.) is a must Understanding of MLOps tools and lifecycle (e.g., MLflow, DVC, monitoring tools) Hands-on experience with time-series analysis and forecasting models for predictive maintenance Experience with LLMs, prompt engineering, and GenAI pipelines Deployment experience using Docker, microservices, and embedded platforms Exposure to model optimization (quantization, pruning) for edge AI Strong understanding of data annotation, synthetic data generation, and active learning workflows Strong grasp of SQL and exposure to NoSQL databases (e.g., Redis, MongoDB) Preferred Skills Experience with LangChain, LlamaIndex, or custom AI agent frameworks Knowledge of digital twins, condition monitoring, or telemetry Knowledge of AI safety, model robustness, and explainability techniques for production-grade systems Familiarity with edge-cloud orchestration and event-driven systems Qualifications Master’s degree in relevant or related field of AI/ML from Tier-I/II institute with 3-4 years of experience If you're passionate about building intelligent systems that power the next generation of smart home devices — from real-time perception to autonomous decision-making — we want to hear from you. Join the AI team at Mantra Softech and help redefine the smart home experience through cutting-edge artificial intelligence. How to Apply Send your resume and portfolio to jatin.prakash@mantratec.com Please include "Senior - AI Engineer" in the subject line.

About the job We are seeking an experienced AI/NLP Engineer to join our team. The ideal candidate will have expertise in working with large language models and AI-based tools, strong analytical skills, and experience developing, testing, and refining AI-driven applications. Know your team (“Legacy Rewired, Engineering the Future”) At ValueMomentum’s Engineering Centre, we are a team of passionate engineers who thrive on tackling complex business challenges with innovative solutions while transforming the P&C insurance value chain. We achieve this through a strong engineering foundation and by continuously refining our processes, methodologies, tools, agile delivery teams, and core engineering archetypes. Our core expertise lies in six key areas: Cloud Engineering, Application Engineering, Data Engineering, Core Engineering, Quality Engineering, and Domain expertise. Relevant Experience should be more than 3 Years on the same Programming: Python, TensorFlow, PyTorch, Scikit-learn ✔ MLOps & Deployment: Docker, Kubernetes, MLflow, Airflow ✔ Cloud: AWS (SageMaker), GCP (Vertex AI), Azure ML ✔ Big Data: Spark, Kafka, Hadoop ✔ Databases: SQL, NoSQL, GraphDBs ✔ DevOps: CI/CD, GitHub Actions, Terraform ✔ Optimization: ONNX, TensorRT, Pruning & Quantization Feature - AI Engineer Focus - Building and deploying AI systems Responsibilities - Developing algorithms, deploying models, ensuring scalability Skills - Strong programming, AI frameworks, cloud computing Goal - Create AI-powered solutions

About this role: Lead Software Engineer (AI) position having experience in classic and generative AI techniques, and responsible for design, implementation, and support of Python based applications to help fulfill our Research & Consulting Delivery strategy. What youll do: Deliver client engagements that use AI rapidly, on the order of a few weeks Stay on top of current tools, techniques, and frameworks to be able to use and advise clients on them Build proofs of concept rapidly, to learn and adapt to changing market needs Support building internal applications for use by associates to improve productivity What you’ll need: 6-8 years of experience in classic AI techniques and at least 1.5 years in generative AI techniques. Demonstrated ability to run short development cycles and solid grasp of building software in a collaborative team setting. Must have: Experience building applications for knowledge search and summarization, frameworks to evaluate and compare performance of different GenAI techniques, measuring and improving accuracy and helpfulness of generative responses, implementing observability. Experience with agentic AI frameworks, RAG, embedding models, vector DBs Experience working with Python libraries like Pandas, Scikit-Learn, Numpy, and Scipy is required. Experience deploying applications to cloud platforms such as Azure and AWS. Solid grasp of building software in a collaborative team setting - use of agile scrum and tools like Jira / GitHub. Nice to have: Experience in finetuning Language models. Familiarity with AWS Bedrock / Azure AI / Databricks Services. Experience in Machine learning models and techniques like NLP, BERT, Transformers, Deep learning. Experience in MLOps Frameworks like Kubeflow, MLFlow, DataRobot, Airflow etc., Experience building scalable data models and performing complex relational databases queries using SQL (Oracle, MySQL, PostgreSQL). Who you are: Excellent written, verbal, and interpersonal communication skills with the ability to present technical information in a clear and concise manner to IT Leaders and business stakeholders. Effective time management skills and ability to meet deadlines. Excellent communications skills interacting with technical and business audiences. Excellent organization, multitasking, and prioritization skills. Must possess a willingness and aptitude to embrace new technologies/ideas and master concepts rapidly. Intellectual curiosity, passion for technology and keeping up with new trends. Delivering project work on-time within budget with high quality. Demonstrated ability to run short development cycle.

Job Title : Data Scientist Location State : Tamil Nadu,Telangana Location City : Hyderabad, Chennai Experience Required : 4 to 6 Year(s) CTC Range : 7 to 11 LPA Shift: Day Shift Work Mode: Onsite Position Type: C2H Openings: 2 Company Name: VARITE INDIA PRIVATE LIMITED About The Client: Client is an Indian multinational technology company specializing in information technology services and consulting. Headquartered in Mumbai, it is a part of the Tata Group and operates in 150 locations across 46 countries. About The Job: Requirements: 5+ years in predictive analytics, with expertise in regression, classification, time-series modeling. Hands-on experience with Databricks Runtime for ML, Spark SQL, and PySpark. Familiarity with MLflow, Feature Store, and Unity Catalog for governance. Industry experience in Life Insurance or P&C. Skills: Python, PySpark , MLflow, Databricks AutoML. Predictive MoClienting (Classification , Clustering , Regression, timeseries and NLP). Cloud platform (Azure/AWS) , Delta Lake, Unity Catalog. Certifications; Databricks Certified ML Practitioner (Optional) Essential Job Functions: Design and deploy predictive models (e.g., forecasting, churn analysis, fraud detection) using Python/SQL, Spark MLlib, and Databricks ML. Build end-to-end ML pipelines (data ingestion, feature engineering, model training, deployment) on Databricks Lakehouse. Optimize model performance via hyperparameter tuning, AutoML, and MLflow tracking. Collaborate with engineering teams to operationalize models (batch/real-time) using Databricks Jobs or REST APIs. Implement Delta Lake for scalable, ACID-compliant data workflows. Enable CI/CD for ML pipelines using Databricks Repos and GitHub Actions. Troubleshoot issues in Spark Jobs and Databricks Environment. Qualifications: Skill Required: Data Science, Python for Data Science Experience Range in Required Skills: 4-6 Years How to Apply: Interested candidates are invited to submit their resume using the apply online button on this job post. About VARITE: VARITE is a global staffing and IT consulting company providing technical consulting and team augmentation services to Fortune 500 Companies in USA, UK, CANADA and INDIA. VARITE is currently a primary and direct vendor to the leading corporations in the verticals of Networking, Cloud Infrastructure, Hardware and Software, Digital Marketing and Media Solutions, Clinical Diagnostics, Utilities, Gaming and Entertainment, and Financial Services. Equal Opportunity Employer: VARITE is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, marital status, veteran status, or disability status. Unlock Rewards: Refer Candidates and Earn. If you're not available or interested in this opportunity, please pass this along to anyone in your network who might be a good fit and interested in our open positions. VARITE offers a Candidate Referral program, where you'll receive a one-time referral bonus based on the following scale if the referred candidate completes a three-month assignment with VARITE. Exp Req - Referral Bonus 0 - 2 Yrs. - INR 5,000 2 - 6 Yrs. - INR 7,500 6 + Yrs. - INR 10,000

Job Title: MLOps Engineer – AWS SageMaker & MLflow (Remote) Location: Fully Remote (India Preferred) Experience Level: 5+ Years Employment Type: Full-Time Company: KrtrimaIQ Cognitive Solutions 📧 Apply at: nikhil.kumar@krtrimaiq.ai Job Summary: KrtrimaIQ Cognitive Solutions is looking for a Senior MLOps Engineer with deep expertise in AWS SageMaker , MLflow , and end-to-end machine learning lifecycle management . The ideal candidate will have hands-on experience in deploying and managing scalable ML solutions in production environments and a passion for building reliable MLOps systems. This is a fully remote opportunity offering flexibility and the chance to work on innovative AI/ML products for global enterprises. Key Responsibilities: Design, build, and maintain scalable and secure MLOps pipelines using AWS SageMaker and MLflow Automate ML model lifecycle: training, testing, tracking, versioning, and deployment to production Implement CI/CD pipelines and DevOps practices for ML infrastructure Ensure reproducibility, monitoring, and performance optimization of deployed models Collaborate closely with Data Scientists, Data Engineers, and DevOps teams to streamline workflows Contribute to MLOps research and explore new tools and frameworks in the production ML space Ensure compliance with best practices in cloud computing , software development , and data security Must-Have Qualifications: 5+ years of professional experience in Software Engineering or MLOps Expertise in AWS , specifically AWS SageMaker for building and deploying ML models Hands-on experience with MLflow for model tracking, versioning, and deployment Strong programming skills in Python (R, Scala, or Spark is a plus) Solid experience in production-grade development and infrastructure automation Strong problem-solving, analytical, and research skills Preferred Qualifications: Experience with AWS DataZone Familiarity with Docker , Kubernetes , Airflow , Terraform , or other orchestration tools Understanding of data versioning , feature stores , and ML monitoring tools Exposure to MLOps research and experimentation in startup/innovation environments What We Offer: 💻 100% Remote Work Flexibility 🌐 Exposure to enterprise-grade AI and MLOps use cases 🤝 Collaborative work culture focused on innovation and learning 🚀 Fast-paced startup-like environment with global project opportunities How to Apply: Send your updated CV to: nikhil.kumar@krtrimaiq.ai

Job Description: Key Responsibilities: Data Engineering & Architecture: Design, develop, and maintain high-performance data pipelines for structured and unstructured data using Azure Data Bricks and Apache Spark. Build and manage scalable data ingestion frameworks for batch and real-time data processing. Implement and optimize data lake architecture in Azure Data Lake to support analytics and reporting workloads. Develop and optimize data models and queries in Azure Synapse Analytics to power BI and analytics use cases. Cloud-Based Data Solutions: Architect and implement modern data lakehouses combining the best of data lakes and data warehouses. Leverage Azure services like Data Factory, Event Hub, and Blob Storage for end-to-end data workflows. Ensure security, compliance, and governance of data through Azure Role-Based Access Control (RBAC) and Data Lake ACLs. ETL/ELT Development: Develop robust ETL/ELT pipelines using Azure Data Factory, Data Bricks notebooks, and PySpark. Perform data transformations, cleansing, and validation to prepare datasets for analysis. Manage and monitor job orchestration, ensuring pipelines run efficiently and reliably. Performance Optimization: Optimize Spark jobs and SQL queries for large-scale data processing. Implement partitioning, caching, and indexing strategies to improve performance and scalability of big data workloads. Conduct capacity planning and recommend infrastructure optimizations for cost-effectiveness. Collaboration & Stakeholder Management: Work closely with business analysts, data scientists, and product teams to understand data requirements and deliver solutions. Participate in cross-functional design sessions to translate business needs into technical specifications. Provide thought leadership on best practices in data engineering and cloud computing. Documentation & Knowledge Sharing: Create detailed documentation for data workflows, pipelines, and architectural decisions. Mentor junior team members and promote a culture of learning and innovation. Required Qualifications: Experience: 7+ years of experience in data engineering, big data, or cloud-based data solutions. Proven expertise with Azure Data Bricks, Azure Data Lake, and Azure Synapse Analytics. Technical Skills: Strong hands-on experience with Apache Spark and distributed data processing frameworks. Advanced proficiency in Python and SQL for data manipulation and pipeline development. Deep understanding of data modeling for OLAP, OLTP, and dimensional data models. Experience with ETL/ELT tools like Azure Data Factory or Informatica. Familiarity with Azure DevOps for CI/CD pipelines and version control. Big Data Ecosystem: Familiarity with Delta Lake for managing big data in Azure. Experience with streaming data frameworks like Kafka, Event Hub, or Spark Streaming. Cloud Expertise: Strong understanding of Azure cloud architecture, including storage, compute, and networking. Knowledge of Azure security best practices, such as encryption and key management. Preferred Skills (Nice to Have): Experience with machine learning pipelines and frameworks like MLFlow or Azure Machine Learning. Knowledge of data visualization tools such as Power BI for creating dashboards and reports. Familiarity with Terraform or ARM templates for infrastructure as code (IaC). Exposure to NoSQL databases like Cosmos DB or MongoDB. Experience with data governance to Weekly Hours: 40 Time Type: Regular Location: Hyderabad, Andhra Pradesh, India It is the policy of AT&T to provide equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. In addition, AT&T will provide reasonable accommodations for qualified individuals with disabilities. AT&T is a fair chance employer and does not initiate a background check until an offer is made.

At CGI, we’re a team of builders. We call our employees members because all who join CGI are building their own company - one that has grown to 72,000 professionals located in 40 countries. Founded in 1976, CGI is a leading IT and business process services firm committed to helping clients succeed. We have the global resources, expertise, stability and dedicated professionals needed to achieve. At CGI, we’re a team of builders. We call our employees members because all who join CGI are building their own company - one that has grown to 72,000 professionals located in 40 countries. Founded in 1976, CGI is a leading IT and business process services firm committed to helping clients succeed. We have the global resources, expertise, stability and dedicated professionals needed to achieve results for our clients - and for our members. Come grow with us. Learn more at www.cgi.com. This is a great opportunity to join a winning team. CGI offers a competitive compensation package with opportunities for growth and professional development. Benefits for full-time, permanent members start on the first day of employment and include a paid time-off program and profit participation and stock purchase plans. We wish to thank all applicants for their interest and effort in applying for this position, however, only candidates selected for interviews will be contacted. No unsolicited agency referrals please. Job Title: MLOPS Data Engineer Position: Senior Software Engineer Experience: 5 - 8 Years Category: Software Development/ Engineering Main location: Bangalore/Hyderabad/Chennai Position ID: J0325-0709 Employment Type: Full Time Works independently under limited supervision and applies knowledge of subject matter in Applications Development. Possess sufficient knowledge and skills to effectively deal with issues, challenges within field of specialization to develop simple applications solutions. Second level professional with direct impact on results and outcome. Qualification: Bachelor's degree in Computer Science or related field or higher with minimum 4 years of relevant experience. Your future duties and responsibilities Development experience in data technologies. Experienced with data wrangling and preparation for use within data science, business intelligence or similar analytical functions required. Experience in data technologies - Hadoop PySpark / Scala (Any one) Experience in Machine Learning. Experience in Database - [ RDBMS(Oracle/Teradata) / Hive - Impala / Mongo] at least two. Experience in Analytics and reporting (Tableau). (Good to have). Coordinate with Team for project deliverables , Lead and document project status meetings Highly organized with good time management skills and Customer service orientation Required qualifications to be successful in this role Position: Senior Software Engineer Experience: 5 - 8 Years Main location: Hyderabad/Bangalore/Chennai Must-Have Skills: Advanced Python programming skills Proven experience implementing machine learning data workflows Proficiency with data technologies including Hadoop, Spark, and Kafka Strong programming background in Java, Scala, and SQL Experience implementing Jenkins CI/CD pipelines Hands-on experience with data engineering in a Cloudera CDP (Cloudera Data Platform) environment. Experience with Spark Structured Streaming for near-real-time data processing Docker and Kubernetes containerization expertise Experience with Hopsworks Feature Store implementation Hands-on experience with cloud platforms (AWS, GCP, or Azure) Experience with MLOps tools and frameworks (e.g., Kubeflow, MLflow, etc.) Familiarity with model versioning, continuous integration, and deployment in machine learning pipeline. Knowledge of data model management and automated testing in machine learning environments Bachelor’s degree in computer science or related field Excellent communication skills and collaborative mindset Good-to-Have Skills: Knowledge on IBM Mainframe- Monitor jobs in CA7 schedular, Create CA7 jobs for automation of data loads Knowledge on DOC05, DOC40 & AGENT will be beneficial Together, as owners, let’s turn meaningful insights into action. Life at CGI is rooted in ownership, teamwork, respect and belonging. Here, you’ll reach your full potential because… You are invited to be an owner from day 1 as we work together to bring our Dream to life. That’s why we call ourselves CGI Partners rather than employees. We benefit from our collective success and actively shape our company’s strategy and direction. Your work creates value. You’ll develop innovative solutions and build relationships with teammates and clients while accessing global capabilities to scale your ideas, embrace new opportunities, and benefit from expansive industry and technology expertise. You’ll shape your career by joining a company built to grow and last. You’ll be supported by leaders who care about your health and well-being and provide you with opportunities to deepen your skills and broaden your horizons. Come join our team—one of the largest IT and business consulting services firms in the world.

Job Description: Key Responsibilities: Data Engineering & Architecture: Design, develop, and maintain high-performance data pipelines for structured and unstructured data using Azure Data Bricks and Apache Spark. Build and manage scalable data ingestion frameworks for batch and real-time data processing. Implement and optimize data lake architecture in Azure Data Lake to support analytics and reporting workloads. Develop and optimize data models and queries in Azure Synapse Analytics to power BI and analytics use cases. Cloud-Based Data Solutions: Architect and implement modern data lakehouses combining the best of data lakes and data warehouses. Leverage Azure services like Data Factory, Event Hub, and Blob Storage for end-to-end data workflows. Ensure security, compliance, and governance of data through Azure Role-Based Access Control (RBAC) and Data Lake ACLs. ETL/ELT Development: Develop robust ETL/ELT pipelines using Azure Data Factory, Data Bricks notebooks, and PySpark. Perform data transformations, cleansing, and validation to prepare datasets for analysis. Manage and monitor job orchestration, ensuring pipelines run efficiently and reliably. Performance Optimization: Optimize Spark jobs and SQL queries for large-scale data processing. Implement partitioning, caching, and indexing strategies to improve performance and scalability of big data workloads. Conduct capacity planning and recommend infrastructure optimizations for cost-effectiveness. Collaboration & Stakeholder Management: Work closely with business analysts, data scientists, and product teams to understand data requirements and deliver solutions. Participate in cross-functional design sessions to translate business needs into technical specifications. Provide thought leadership on best practices in data engineering and cloud computing. Documentation & Knowledge Sharing: Create detailed documentation for data workflows, pipelines, and architectural decisions. Mentor junior team members and promote a culture of learning and innovation. Required Qualifications: Experience: 7+ years of experience in data engineering, big data, or cloud-based data solutions. Proven expertise with Azure Data Bricks, Azure Data Lake, and Azure Synapse Analytics. Technical Skills: Strong hands-on experience with Apache Spark and distributed data processing frameworks. Advanced proficiency in Python and SQL for data manipulation and pipeline development. Deep understanding of data modeling for OLAP, OLTP, and dimensional data models. Experience with ETL/ELT tools like Azure Data Factory or Informatica. Familiarity with Azure DevOps for CI/CD pipelines and version control. Big Data Ecosystem: Familiarity with Delta Lake for managing big data in Azure. Experience with streaming data frameworks like Kafka, Event Hub, or Spark Streaming. Cloud Expertise: Strong understanding of Azure cloud architecture, including storage, compute, and networking. Knowledge of Azure security best practices, such as encryption and key management. Preferred Skills (Nice to Have): Experience with machine learning pipelines and frameworks like MLFlow or Azure Machine Learning. Knowledge of data visualization tools such as Power BI for creating dashboards and reports. Familiarity with Terraform or ARM templates for infrastructure as code (IaC). Exposure to NoSQL databases like Cosmos DB or MongoDB. Experience with data governance to Weekly Hours: 40 Time Type: Regular Location: Hyderabad, Andhra Pradesh, India It is the policy of AT&T to provide equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. In addition, AT&T will provide reasonable accommodations for qualified individuals with disabilities. AT&T is a fair chance employer and does not initiate a background check until an offer is made.

Company Description NielsenIQ is a consumer intelligence company that delivers the Full View™, the world’s most complete and clear understanding of consumer buying behavior that reveals new pathways to growth. Since 1923, NIQ has moved measurement forward for industries and economies across the globe. We are putting the brightest and most dedicated minds together to accelerate progress. Our diversity brings out the best in each other so we can leave a lasting legacy on the work that we do and the people that we do it with. NielsenIQ offers a range of products and services that leverage Machine Learning and Artificial Intelligence to provide insights into consumer behavior and market trends. This position opens the opportunity to apply the latest state of the art in AI/ML and data science to global and key strategic projects Job Description We are looking for a Research Scientist with a data-centric mindset to join our applied research and innovation team. The ideal candidate will have a strong background in machine learning, deep learning, operationalization of AI/ML and process automation. You will be responsible for analyzing data, researching the most appropriate techniques, and the development, testing, support and delivery of proof of concepts to resolve real-world and large-scale challenging problems. Job Responsibilities Develop and apply machine learning innovations with minimal technical supervision. Understand the requirements from stakeholders and be able to communicate results and conclusions in a way that is accurate, clear and winsome. Perform feasibility studies and analyse data to determine the most appropriate solution. Work on many different data challenges, always ensuring a combination of simplicity, scalability, reproducibility and maintainability within the ML solutions and source code. Both data and software must be developed and maintained with high-quality standards and minimal defects. Collaborate with other technical fellows on the integration and deployment of ML solutions. To work as a member of a team, encouraging team building, motivation and cultivating effective team relations. Qualifications Essential Requirements Bachelor's degree in Computer Science or an equivalent numerate discipline Demonstrated senior experience in Machine Learning, Deep Learning & other AI fields Experience working with large datasets, production-grade code & operationalization of ML solutions EDA analysis & practical hands-on experience with datasets, ML models (Pytorch or Tensorflow) & evaluations Able to understand scientific papers & develop the idea into executable code Analytical mindset, problem solving & logical thinking capabilities Proactive attitude, constructive, intellectual curiosity & persistence to find answers to questions A high level of interpersonal & communication skills in English & strong ability to meet deadlines Python, Pytorch, Git, pandas, dask, polars, sklearn, huggingface, docker, databricks Desired Skills Masters degree &/or specialization courses in AI/ML. PhD in science is an added value Experience in MLOPs (MLFlow, Prefect) & deployment of AI/ML solutions to the cloud (Azure preferred) Understanding & practice of LLMs & Generative AI (prompt engineering, RAG) Experience with Robotic Process Automation, Time Series Forecasting & Predictive modeling A practical grasp of databases (SQL, ElasticSearch, Pinecone, Faiss) Previous experience in retail, consumer, ecommerce, business, FMCG products (NielsenIQ portfolio) Additional Information With @NielsenIQ, we’re now an even more diverse team of 40,000 people – each with their own stories Our increasingly diverse workforce empowers us to better reflect the diversity of the markets we measure. Our Benefits Flexible working environment Volunteer time off LinkedIn Learning Employee-Assistance-Program (EAP) Our Benefits Flexible working environment Volunteer time off LinkedIn Learning Employee-Assistance-Program (EAP) About NIQ NIQ is the world’s leading consumer intelligence company, delivering the most complete understanding of consumer buying behavior and revealing new pathways to growth. In 2023, NIQ combined with GfK, bringing together the two industry leaders with unparalleled global reach. With a holistic retail read and the most comprehensive consumer insights—delivered with advanced analytics through state-of-the-art platforms—NIQ delivers the Full View™. NIQ is an Advent International portfolio company with operations in 100+ markets, covering more than 90% of the world’s population. For more information, visit NIQ.com Want to keep up with our latest updates? Follow us on: LinkedIn | Instagram | Twitter | Facebook Our commitment to Diversity, Equity, and Inclusion NIQ is committed to reflecting the diversity of the clients, communities, and markets we measure within our own workforce. We exist to count everyone and are on a mission to systematically embed inclusion and diversity into all aspects of our workforce, measurement, and products. We enthusiastically invite candidates who share that mission to join us. We are proud to be an Equal Opportunity/Affirmative Action-Employer, making decisions without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability status, age, marital status, protected veteran status or any other protected class. Our global non-discrimination policy covers these protected classes in every market in which we do business worldwide. Learn more about how we are driving diversity and inclusion in everything we do by visiting the NIQ News Center: https://nielseniq.com/global/en/news-center/diversity-inclusion

Experience : 2.00 + years Salary : INR 1500000-2500000 / year (based on experience) Expected Notice Period : 30 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Office (Pune) Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Anervea.AI) (*Note: This is a requirement for one of Uplers' client - Anervea.AI) What do you need for this opportunity? Must have skills required: Airflow, LLMs, NLP, Statistical Modeling, Predictive Analysis, Forecasting, Python, SQL, MLFlow, pandas, Scikit-learn, XgBoost Anervea.AI is Looking for: As an ML / Data Science Engineer at Anervea, you’ll work on designing, training, deploying, and maintaining machine learning models across multiple products. You’ll build models that predict clinical trial outcomes, extract insights from structured and unstructured healthcare data, and support real-time scoring for sales or market access use cases. You’ll collaborate closely with AI engineers, backend developers, and product owners to translate data into product features that are explainable, reliable, and impactful. Key Responsibilities Develop and optimize predictive models using algorithms such as XGBoost, Random Forest, Logistic Regression, and ensemble methods Engineer features from real-world healthcare data (clinical trials, treatment adoption, medical events, digital behavior) Analyze datasets from sources like ClinicalTrials.gov, PubMed, Komodo, Apollo.io, and internal survey pipelines Build end-to-end ML pipelines for inference and batch scoring Collaborate with AI engineers to integrate LLM-generated features with traditional models Ensure explainability and robustness of models using SHAP, LIME, or custom logic Validate models against real-world outcomes and client feedback Prepare clean, structured datasets using SQL and Pandas Communicate insights clearly to product, business, and domain teams Document all processes, assumptions, and model outputs thoroughly Technical Skills Required : Strong programming skills in Python (NumPy, Pandas, scikit-learn, XGBoost, LightGBM) Experience with statistical modeling and classification algorithms Solid understanding of feature engineering, model evaluation, and validation techniques Exposure to real-world healthcare, trial, or patient data (strong bonus) Comfortable working with unstructured data and data cleaning techniques Knowledge of SQL and NoSQL databases Familiarity with ML lifecycle tools (MLflow, Airflow, or similar) Bonus: experience working alongside LLMs or incorporating generative features into ML Bonus: knowledge of NLP preprocessing, embeddings, or vector similarity methods Personal Attributes : Strong analytical and problem-solving mindset Ability to convert abstract questions into measurable models Attention to detail and high standards for model quality Willingness to learn life sciences concepts relevant to each use case Clear communicator who can simplify complexity for product and business teams Independent learner who actively follows new trends in ML and data science Reliable, accountable, and driven by outcomes—not just code Bonus Qualities : Experience building models for healthcare, pharma, or biotech Published work or open-source contributions in data science Strong business intuition on how to turn models into product decisions How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

We are seeking a skilled Lead Software Engineer to join our team and lead a project focused on developing GenAI applications using Large Language Models (LLMs) and Python programming . In this role, you will be responsible for designing and optimizing Al-generated text prompts to maximize effectiveness for various applications. You will also collaborate with cross-functional teams to ensure seamless integration of optimized prompts into the overall product or system. Your expertise in prompt engineering principles and techniques will allow you to guide models to desired outcomes and evaluate prompt performance to identify areas for optimization and iteration. Responsibilities Design, develop, test and refine AI-generated text prompts to maximize effectiveness for various applications Ensure seamless integration of optimized prompts into the overall product or system Rigorously evaluate prompt performance using metrics and user feedback Collaborate with cross-functional teams to understand requirements and ensure prompts align with business goals and user needs Document prompt engineering processes and outcomes, educate teams on prompt best practices and keep updated on the latest AI advancements to bring innovative solutions to the project Requirements 7 to 12 years of relevant professional experience Expertise in Python programming including experience with Al/machine learning frameworks like TensorFlow, PyTorch, Keras, Langchain, MLflow, Promtflow 2-5 years of working knowledge of NLP and LLMs like BERT, GPT-3/4, T5, etc. Knowledge of how these models work and how to fine-tune them Expertise in prompt engineering principles and techniques like chain of thought, in-context learning, tree of thought, etc. Knowledge of retrieval augmented generation (RAG) Strong analytical and problem-solving skills with the ability to think critically and troubleshoot issues Excellent communication skills, both verbal and written in English at a B2+ level for collaborating across teams, explaining technical concepts, and documenting work outcomes

As a trusted global transformation partner, Welocalize accelerates the global business journey by enabling brands and companies to reach, engage, and grow international audiences. Welocalize delivers multilingual content transformation services in translation, localization, and adaptation for over 250 languages with a growing network of over 400,000 in-country linguistic resources. Driving innovation in language services, Welocalize delivers high-quality training data transformation solutions for NLP-enabled machine learning by blending technology and human intelligence to collect, annotate, and evaluate all content types. Our team works across locations in North America, Europe, and Asia serving our global clients in the markets that matter to them. www.welocalize.com To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Job Reference: Role Summary: The AIML Platform Engineering Lead is a pivotal leadership role responsible for managing the day-to-day operations and development of the AI/ML platform team. In this role, you will guide the team in designing, building, and maintaining scalable platforms, while collaborating with other engineering and data science teams to ensure successful model deployment and lifecycle management. Key Responsibilities: Lead and manage a team of platform engineers in developing and maintaining robust AI/ML platforms Define and implement best practices for machine learning infrastructure, ensuring scalability, performance, and security Collaborate closely with data scientists and DevOps teams to optimize the ML lifecycle from model training to deployment Establish and enforce standards for platform automation, monitoring, and operational efficiency Serve as the primary liaison between engineering teams, product teams, and leadership Mentor and develop junior engineers, providing technical guidance and performance feedback Stay abreast of the latest advancements in AI/ML infrastructure and integrate new technologies where applicable Qualifications: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field 8+ years of experience in Python & Node.js development and infrastructure Proven experience in leading engineering teams and driving large-scale projects Extensive expertise in cloud infrastructure (AWS, GCP, Azure), MLOps tools (e.g., Kubeflow, MLflow), and infrastructure as code (Terraform) Strong programming skills in Python and Node.js, with a proven track record of building scalable and maintainable systems that support AI/ML workflows Hands-on experience with monitoring and observability tools, such as Datadog, to ensure platform reliability and performance Strong leadership and communication skills with the ability to influence cross-functional teams Excellent problem-solving skills and the ability to work in a fast-paced, collaborative environment

About Netskope Today, there's more data and users outside the enterprise than inside, causing the network perimeter as we know it to dissolve. We realized a new perimeter was needed, one that is built in the cloud and follows and protects data wherever it goes, so we started Netskope to redefine Cloud, Network and Data Security. Since 2012, we have built the market-leading cloud security company and an award-winning culture powered by hundreds of employees spread across offices in Santa Clara, St. Louis, Bangalore, London, Paris, Melbourne, Taipei, and Tokyo. Our core values are openness, honesty, and transparency, and we purposely developed our open desk layouts and large meeting spaces to support and promote partnerships, collaboration, and teamwork. From catered lunches and office celebrations to employee recognition events and social professional groups such as the Awesome Women of Netskope (AWON), we strive to keep work fun, supportive and interactive. Visit us at Netskope Careers. Please follow us on LinkedIn and Twitter@Netskope. About The Role Please note, this team is hiring across all levels and candidates are individually assessed and appropriately leveled based upon their skills and experience. The Data Engineering team builds and optimizes systems spanning data ingestion, processing, storage optimization and more. We work closely with engineers and the product team to build highly scalable systems that tackle real-world data problems and provide our customers with accurate, real-time, fault tolerant solutions to their ever-growing data needs. We support various OLTP and analytics environments, including our Advanced Analytics and Digital Experience Management products. We are looking for skilled engineers experienced with building and optimizing cloud-scale distributed systems to develop our next-generation ingestion, processing and storage solutions. You will work closely with other engineers and the product team to build highly scalable systems that tackle real-world data problems. Our customers depend on us to provide accurate, real-time and fault tolerant solutions to their ever growing data needs. This is a hands-on, impactful role that will help lead development, validation, publishing and maintenance of logical and physical data models that support various OLTP and analytics environments. What's In It For You You will be part of a growing team of renowned industry experts in the exciting space of Data and Cloud Analytics Your contributions will have a major impact on our global customer-base and across the industry through our market-leading products You will solve complex, interesting challenges, and improve the depth and breadth of your technical and business skills. What You Will Be Doing Lead the design, development, and deployment of AI/ML models for threat detection, anomaly detection, and predictive analytics in cloud and network security. Architect and implement scalable data pipelines for processing large-scale datasets from logs, network traffic, and cloud environments. Apply MLOps best practices to deploy and monitor machine learning models in production. Collaborate with cloud architects and security analysts to develop cloud-native security solutions leveraging platforms like AWS, Azure, or GCP. Build and optimize Retrieval-Augmented Generation (RAG) systems by integrating large language models (LLMs) with vector databases for real-time, context-aware applications. Analyze network traffic, log data, and other telemetry to identify and mitigate cybersecurity threats. Ensure data quality, integrity, and compliance with GDPR, HIPAA, or SOC 2 standards. Drive innovation by integrating the latest AI/ML techniques into security products and services. Mentor junior engineers and provide technical leadership across projects. Required Skills And Experience AI/ML Expertise Proficiency in advanced machine learning techniques, including neural networks (e.g., CNNs, Transformers) and anomaly detection. Experience with AI frameworks like TensorFlow, PyTorch, and Scikit-learn. Strong understanding of MLOps practices and tools (e.g., MLflow, Kubeflow). Experience building and deploying Retrieval-Augmented Generation (RAG) systems, including integration with LLMs and vector databases. Data Engineering Expertise designing and optimizing ETL/ELT pipelines for large-scale data processing. Hands-on experience with big data technologies (e.g., Apache Spark, Kafka, Flink). Proficiency in working with relational and non-relational databases, including ClickHouse and BigQuery. Familiarity with vector databases such as Pinecone and PGVector and their application in RAG systems. Experience with cloud-native data tools like AWS Glue, BigQuery, or Snowflake. Cloud and Security Knowledge Strong understanding of cloud platforms (AWS, Azure, GCP) and their services. Experience with network security concepts, extended detection and response, and threat modeling. Software Engineering Proficiency in Python, Java, or Scala for data and ML solution development. Expertise in scalable system design and performance optimization for high-throughput applications. Leadership and Collaboration Proven ability to lead cross-functional teams and mentor engineers. Strong communication skills to present complex technical concepts to stakeholders. Education BSCS or equivalent required, MSCS or equivalent strongly preferred Netskope is committed to implementing equal employment opportunities for all employees and applicants for employment. Netskope does not discriminate in employment opportunities or practices based on religion, race, color, sex, marital or veteran statues, age, national origin, ancestry, physical or mental disability, medical condition, sexual orientation, gender identity/expression, genetic information, pregnancy (including childbirth, lactation and related medical conditions), or any other characteristic protected by the laws or regulations of any jurisdiction in which we operate. Netskope respects your privacy and is committed to protecting the personal information you share with us, please refer to Netskope's Privacy Policy for more details.

Job Title: Computer Vision Engineer Location: Coimbatore, Work from office role Experience Required: 2+ years Employment Type: Full-Time, Permanent Company: Katomaran Technologies About Us Katomaran Technologies is a cutting-edge technology company building real-world AI applications that span across computer vision, large language models (LLMs), and AI agentic systems. We are looking for a highly motivated Senior AI Developer who thrives at the intersection of technology, leadership, and innovation. You will play a core role in architecting AI products, leading engineering teams, and collaborating directly with the founding team and customers to turn vision into scalable, production-ready solutions. Key Responsilbilities Architect and develop scalable AI solutions using computer vision, LLMs, and agent-based AI architectures. Collaborate with the founding team to define product roadmaps and AI strategy. Lead and mentor a team of AI and software engineers, ensuring high code quality and project delivery timelines. Develop robust, efficient pipelines for model training, validation, deployment, and real-time inference. Work closely with customers and internal stakeholders to translate requirements into AI-powered applications. Stay up to date with state-of-the-art research in vision models (YOLO, SAM, CLIP, etc.), transformers, and agentic systems (AutoGPT-style orchestration). Optimize AI models for deployment on cloud and edge environments. Required Skills and Qualifications Bachelor’s or Master’s in Computer Science, AI, Machine Learning, or related fields. 2+ years of hands-on experience building AI applications in computer vision and/or NLP. Strong knowledge of Deep Learning frameworks (PyTorch, TensorFlow, OpenCV, HuggingFace, etc.). Proven experience with LLM fine-tuning, prompt engineering, and embedding-based retrieval (RAG). Solid understanding of agentic systems such as LangGraph, CrewAI, AutoGen, or custom orchestrators. Ability to design and manage production-grade AI systems (Docker, REST APIs, GPU optimization, etc.). Strong communication and leadership skills, with experience managing small to mid-size teams. Startup mindset – self-driven, ownership-oriented, and comfortable in ambiguity. Nice to have Experience with video analytics platforms or edge deployment (Jetson, Coral, etc.). Experience with programming skills in C++ will be an added advantage Knowledge of MLOps practices and tools (MLflow, Weights & Biases, ClearML, etc.). Exposure to Reinforcement Learning or multi-agent collaboration models. Customer-facing experience or involvement in AI product strategy. What we offer Medical insurance Paid sick time Paid time off PF To Apply: Send your resume, GitHub/portfolio, and a brief note about your most exciting AI project to hr@katomaran.com.

Job Summary We are seeking a highly skilled and self-motivated AI Engineer to join us as we establish our AI Center of Excellence (CoE). As an early team member, you will play a critical role in shaping the foundation, strategy, and implementation of AI and ML solutions across the organization. This role offers a unique opportunity to work at the forefront of AI innovation, contribute to impactful use cases, and collaborate with cross-functional teams to build intelligent agentic systems. You will work with both Microsoft technologies (Copilot Studio, AI Foundry, Azure OpenAI) and open-source frameworks to design, deploy, and manage enterprise-ready AI solutions. Key Responsibilities a. Design, develop, and deploy AI agents using Microsoft Copilot Studio and AI Foundry. b. Build and fine-tune machine learning models for NLP, prediction, classification, and recommendation tasks. c. Conduct exploratory data analysis (EDA) to extract insights and support model development. d. Implement and manage LLM workflows, including prompt engineering, fine-tuning, evaluation, deployment, and monitoring. e. Utilize open-source frameworks such as LangChain, Hugging Face, MLflow, and RAG pipelines to build scalable, modular AI solutions. f. Integrate AI solutions with business workflows using APIs and cloud-native deployment methods. g. Use Azure AI services, including AI Foundry and Azure OpenAI, for secure and scalable model operations. h. Contribute to the creation of an AI governance framework, including Responsible AI principles, model explainability, fairness, and accountability. i. Support the creation of standards, reusable assets, and documentation as the CoE grows. j. Collaborate with engineering, data, and business teams to define problems, build solutions, and demonstrate value. k. Stay up to date with emerging AI capabilities such as Model Context Protocol (MCP), Agent-to-Agent (A2A) frameworks, and Agent Communication Protocols (ACP), and proactively evaluate opportunities to integrate them into enterprise solutions. Required Qualifications · Bachelor's or master's degree in computer science, Data Science, Engineering, or a related field. · 5+ years of experience in AI, machine learning, or data science with production-level deployments. · Strong foundation in statistics, ML algorithms, and data analysis techniques. · Hands-on experience building with LLMs, GenAI platforms, and AI copilots. · Proficient in Python, with experience using libraries such as Pandas, Scikit-learn, PyTorch, TensorFlow, and Transformers. · Experience with Microsoft Copilot Studio, AI Foundry, and Azure OpenAI. · Working knowledge of open-source GenAI tools (LangChain, Haystack, MLflow). · Understanding of cloud deployment, API integration, and version control (Git).

AI/ML ENGINEER Who We Are? Cleantech Industry Resources accelerates United States solar, battery storage and EV projects by providing turnkey development as a service including 100% internal systems engineering. The company deploys a leading team that spun out of the largest solar power producer in the world. This team operates within a sophisticated suite of software to support projects from land origination, through to commercial operation. Location Chennai What We Offer Opportunity to join a top-notch, collaborative team of professionals Fantastic team environment and collaborative culture Professional development opportunities to grow into an industry leader Medical Insurance for the employee and family Spot Recognition bonus for exceptional performance Long Term Incentive policy Regular team outings, events, and activities to foster a positive work environment Our Commitment to Diversity At CIR, we are dedicated to nurturing a diverse and equitable workforce that truly reflects our community. We deeply value each person’s unique perspective, skills, and experiences. CIR embraces all individuals, regardless of race, religion, sexual orientation, gender identity, age, or nationality. We are steadfast in our commitment to fostering a just and inclusive world through intentional policies and actions. Your individuality enriches our collective strength, and we strive to ensure everyone feels respected, valued, and empowered. Position Summary We are looking for an AI/ML Engineer to build and optimize machine learning models for GIS-based spatial analysis and data-driven decision-making. This role involves working on geospatial AI models, data pipelines, and Retrieval-Augmented Generation (RAG)-based applications for zoning, county sentiment analysis, and regulatory insights. The engineer will also work closely with the data team, leading efforts in data curation and building robust data pipelines to collect, preprocess, and analyse extensive datasets from various geospatial and regulatory sources to generate automated reports and insights. Core Responsibilities Machine Learning for GIS & Spatial Analysis: Develop and deploy ML models for geospatial data processing, forecasting, and automated GIS insights. Work with large-scale geospatial datasets (e.g., satellite imagery, shapefiles, raster/vector data). Create AI models for land classification, feature detection, and geospatial pattern analysis. Optimize spatial data pipelines and build predictive models for environmental and energy sector applications. Retrieval-Augmented Generation (RAG) & NLP Development: Develop RAG-based AI applications to extract insights from zoning, permitting, and regulatory documents. Build LLM-based applications for zoning law interpretation, county sentiment analysis, and compliance predictions. Implement document retrieval and summarization techniques for legal, policy, and energy development reports. Data Engineering & Pipeline Development: Lead the creation of ETL pipelines to collect and preprocess geospatial data for ML model training. Work with PostGIS, PostgreSQL, and cloud storage to manage structured and unstructured data. Collaborate with the data team to design and implement efficient data processing and storage solutions. AI Model Optimization & Deployment: Fine-tune LLMs for domain-specific applications in renewable energy and urban planning. Deploy AI models using cloud-based MLOps frameworks (AWS, GCP, Azure). Optimize ML model inference for real-time GIS applications and geospatial data analysis. Collaboration & Continuous Improvement: Work with cross-functional teams to ensure seamless AI integration with existing business processes. Engage in knowledge sharing and mentoring within the company. Stay updated with latest advancements in AI, GIS, and NLP to improve existing models and solutions. Education Requirements Master’s in Computer Science, Data Science, Machine Learning, Geostatistics, or related fields. Technical Skills and Experience Software Proficiency: Programming: Python (TensorFlow, PyTorch, scikit-learn, pandas, NumPy), SQL. Machine Learning & AI: Deep learning, NLP, retrieval-based AI, geospatial AI, predictive modeling. GIS & Spatial Data Processing: Experience with PostGIS, GDAL, GeoPandas, QGIS, Google Earth Engine. LLM & RAG Development: Experience in fine-tuning LLMs, retrieval models, vector databases (FAISS, Weaviate). Cloud & MLOps: AWS/GCP/Azure, Docker, Kubernetes, MLflow, FastAPI. Big Data Processing: Experience with large-scale data mining, data annotation, and knowledge graph techniques. Database & Storage: PostgreSQL, NoSQL, vector databases, cloud storage solutions. Communication: Strong ability to explain complex AI/ML concepts to non-technical stakeholders. Project Management: Design experience in projects from conception to implementation. Ability to coordinate with other engineers and stakeholders. Renewable Energy Systems: Understanding of solar energy systems and their integration into existing infrastructure Experience 2-4 years of experience Experience in developing AI for energy sector, urban planning, or environmental analysis. Strong understanding of potential prediction, zoning laws, and regulatory compliance AI applications. Familiarity with spatiotemporal ML models and satellite-based geospatial analytics. Psychosocial Skills /Human Skills/Behavioural Skills Strong analytical, organizational, and problem-solving skills. Management experience a plus. Must be a go-getter with an enterprising attitude A self-starter, able to demonstrate high levels of initiative and motivation Entrepreneurial mindset with the ability to take ideas and run with them from concept to conclusion. Technical understanding of clean energy business processes Exceptional verbal and writing communication skills with superiors, peers, partners, and other stakeholders. Excellent interpersonal skills while managing multiple priorities in a fast-paced and ever-changing environment. Physical Demands The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. The physical demands of this job require an individual to be able to work at a computer for most of the day, be able to participate in conference calls and travel to team retreats on a time-to-time basis. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Work Conditions The work environment is usually quiet (normal city traffic noises are common), a blend of artificial and natural light, temperate and generally supports a collaborative work environment. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Equal Opportunity Employer At Cleantech Industry Resources, we embrace diversity and uphold a strong dedication to establishing an all-encompassing atmosphere for both our staff and associates. Our choices in employment are free from any bias related to race, creed, nationality, ethnicity, gender, sexual orientation, gender identity, gender expression, age, physical limitations, veteran status, or any other legally safeguarded attributes. Being an integral part of Cleantech Industry Resources means you can expect to be immersed in a realm of professional possibilities within a culture that nurtures teamwork, adaptability, and the embracing of all.

Exp : 15yrs to 23yrs Primary skills :- Vision AI Solution, Nvidia, Computer Vision, Media, Open Stack. Key Responsibilities Define and lead the end-to-end technical architecture for vision-based AI systems across edge and cloud. Design and optimize large-scale video analytics pipelines using NVIDIA DeepStream, TensorRT, and Triton Inference Server. Architect distributed AI systems, including model training, deployment, inferencing, monitoring, and continuous learning. Collaborate with product, research, and engineering teams to translate business requirements into scalable AI solutions. Lead efforts in model optimization (quantization, pruning, distillation) for real-time performance on devices like Jetson Orin/Xavier. Drive the integration of multi-modal AI (vision + language, 3D, audio) where applicable. Guide platform choices (e.g., edge AI vs cloud AI trade-offs), ensuring cost-performance balance. Mentor senior engineers and promote best practices in MLOps, system reliability, and AI observability. Stay current with emerging technologies (e.g., NeRF, Diffusion Models, Vision Transformers, synthetic data). Contribute to internal innovation strategy, including IP generation, publications, and external presentations. ________________________________________ 🛠️ Required Technical Skills Deep expertise in computer vision, deep learning, and multi-modal AI. Proven hands-on experience with: NVIDIA Jetson, DeepStream SDK, TensorRT, Triton Inference Server TAO Toolkit, Isaac SDK, CUDA, cuDNN Strong in PyTorch, TensorFlow, OpenCV, GStreamer, and GPU-accelerated pipelines. Experience deploying vision AI models at large scale (e.g., 1000+ cameras/devices or multi-GPU clusters). Skilled in cloud-native ML infrastructure: Docker, Kubernetes, CI/CD, MLflow, Seldon, Airflow Proficiency in Python, C++, CUDA (or PyCUDA), and scripting. Familiar with 3D vision, synthetic data pipelines, and generative models (e.g., SAM, NeRF, Diffusion). Experience in multi modal (LVM/VLM), SLMs, small LVM/ VLM, Time series Gen AI models, Agentic AI, LLMOps/Edge LLMOps, Guardrails, Security in Gen AI, YOLO/Vision Transformers ________________________________________ 🤝 Soft Skills & Leadership 10+ years in AI/ML/Computer Vision, with 8+ years in technical leadership or architect roles Strong leadership skills with experience mentoring technical teams and driving innovation. Excellent communicator with the ability to engage stakeholders across engineering, product, and business. Strategic thinker with a practical mindset—able to balance innovation with production-readiness. Experience interfacing with enterprise customers, researchers, and hardware partners. ________________________________________ 🧩 Preferred Qualifications MS or PhD in Computer Vision, Machine Learning, Robotics, or a related technical field ( Added Advantage ) Experience with NVIDIA Omniverse, Clara, or MONAI for healthcare or simulation environments. Experience in domains like smart cities, robotics, retail analytics, or medical imaging. Contributions to open-source projects or technical publications. Certifications: NVIDIA Jetson Developer, AWS/GCP AI/ML Certifications.

Job Title: AI/ML Engineer Experience: 4+ Years Location: Remote Job Type: Full-Time Job Summary: We are looking for a passionate and results-driven AI/ML Engineer with 4 years of experience in designing, building, and deploying machine learning models and intelligent systems. The ideal candidate should have solid programming skills, a strong grasp of data preprocessing, model evaluation, and MLOps practices. You will collaborate with cross-functional teams including data scientists, software engineers, and product managers to integrate intelligent features into applications and systems. Key Responsibilities: Design, develop, train, and optimize machine learning and deep learning models for real-world applications. Preprocess, clean, and transform structured and unstructured data for model training and evaluation. Implement, test, and deploy models using APIs or microservices (Flask, FastAPI, etc.) in production environments. Use ML libraries and frameworks like Scikit-learn, TensorFlow, PyTorch, Hugging Face, XGBoost, etc. Monitor and retrain models as needed for performance, accuracy, and drift mitigation. Collaborate with software and data engineering teams to operationalize ML solutions using MLOps tools. Stay updated with emerging trends in AI/ML and suggest enhancements to existing systems. Required Skills and Qualifications: Bachelor’s or Master’s in Computer Science, Engineering, AI/ML, Data Science, or related field. 4+ years of hands-on experience in machine learning model development and deployment. Strong experience in Python and libraries like Pandas, NumPy, Scikit-learn, Matplotlib/Seaborn. Experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras. Proficiency in model deployment using Flask, FastAPI, Docker, and REST APIs. Experience with version control (Git), model versioning, and experiment tracking (MLflow, Weights & Biases). Familiarity with cloud platforms like AWS (SageMaker), Azure ML, or GCP AI Platform. Knowledge of databases (SQL/NoSQL) and data pipelines (Airflow, Spark, etc.). Strong problem-solving and debugging skills, with an analytical mindset.

Are you passionate about building scalable AI/ML systems and ensuring their success in production? We’re looking for an MLOps Engineer to join our growing AI/ML team. In this role, you’ll support the end-to-end lifecycle of AI/ML and GenAI use cases — from development to deployment and performance monitoring. Work Profile: - Support AI/ML/GenAI use case development, deployment, and monitoring - Implement AI observability tools to track model performance, drift, and health - Collaborate with cross-functional teams and manage stakeholder communications - Create technical documentation, onboarding guides, and monitoring dashboards - Work with cloud platforms (AWS, Azure, GCP) and scripting tools for automation Skills Required: 🔹 3+ years of experience in AI/ML, GenAI, or MLOps roles 🔹 Solid knowledge of AI observability tools (e.g., MLflow, Evidently, Arize) 🔹 Hands-on experience with cloud tools and platforms 🔹 Proficiency in Python, Bash , or similar scripting languages 🔹 Strong communication and stakeholder management skills Bonus If You Have: - Experience working with LLM/GenAI models - Familiarity with orchestration tools (Airflow, Kubeflow) - Exposure to responsible AI or compliance monitoring frameworks

Principal Data Scientist Experience : 14-16 years Job Summary We are seeking a highly experienced AI Lead - Principal Data Scientist to spearhead the delivery of multiple AI and machine learning projects across industries such as supply chain, logistics, pricing, manufacturing, and workforce planning. This role combines deep hands-on expertise in AI/ML/Gen AI (50%) with strategic leadership and cross-functional stakeholder management. You will lead enterprise AI solutions from concept to production, architect scalable cloud-native platforms, and collaborate with business and technology teams to deliver measurable business outcomes. Key Responsibilities Technical Leadership & Solutioning : Design, build, and deploy advanced AI, machine learning, deep learning, and Gen AI solutions using Python, Scikit-learn, TensorFlow/PyTorch, and LangChain/OpenAI APIs. Architect and implement end-to-end AI systems including data ingestion, preprocessing, model training, validation, and deployment. Develop modular, reusable components and APIs (FastAPI/Flask) for inference and integration with digital applications. Lead cloud-native development on AWS, Azure, or GCP for scalable deployment of AI models and pipelines. Project & Delivery Ownership Manage the delivery of multiple concurrent AI/ML/Gen AI initiatives, ensuring quality, timeliness, and business alignment. Define technical roadmap, sprint plans, and milestone goals; track delivery KPIs and model performance in production. Guide agile teams through best practices in model lifecycle management, DevOps/MLOps, and reusable IP development. Business Engagement & Techno-Functional Consulting Act as the techno-functional bridge between business and engineering teams to translate high-level problems into AI/ML use cases. Conduct business value assessments, requirement workshops, and stakeholder reviews. Drive adoption by presenting explainable AI results using visual storytelling and decision support tools. Team Enablement & Innovation Mentor and upskill junior data scientists and engineers in best practices, new AI trends, and real-world problem-solving. Stay current with the latest trends in Generative AI, LLMs, Vision AI, and responsible AI practices. Contribute to internal frameworks, accelerators, and reusable artifacts for faster go-to-market. Required Skills & Qualifications Bachelor's or Master's in Computer Science, AI/ML, Data Science, or related quantitative field. 10-13 years of experience in delivering AI/ML solutions at scale with at least 5 years in a lead or principal role. Hands-on expertise in Python, ML/DL frameworks (TensorFlow, PyTorch, Scikit-learn) and Generative AI (OpenAI, Llama, LangChain). Strong cloud development experience with AWS, GCP, or Azure, including AI/ML services and containerized deployments. Experience deploying models in production via APIs and integrating with enterprise applications. Excellent communication, stakeholder management, and problem-solving skills. Preferred Qualifications Experience in Generative AI (LLMs, prompt engineering, RAG pipelines). Familiarity with MLOps tools (MLflow, Airflow, DVC, Kubeflow). Working knowledge of data engineering workflows, feature stores, and streaming/batch data pipelines. Exposure to data visualization tools like Streamlit, Dash, or Power BI for presenting insights. Certifications in cloud (AWS/GCP/Azure), AI/ML, or data science. (ref:hirist.tech)

Responsibilities : About Lexmark: Founded in 1991 and headquartered in Lexington, Kentucky, Lexmark is recognized as a global leader in print hardware, service, software solutions and security by many of the technology industry’s leading market analyst firms. Lexmark creates cloud-enabled imaging and IoT solutions that help customers in more than 170 countries worldwide quickly realize business outcomes. Lexmark’s digital transformation objectives accelerate business transformation, turning information into insights, data into decisions, and analytics into action. Lexmark India, located in Kolkata, is one of the research and development centers of Lexmark International Inc. The India team works on cutting edge technologies & domains like cloud, AI/ML, Data science, IoT, Cyber security on creating innovative solutions for our customers and helping them minimize the cost and IT burden in providing a secure, reliable, and productive print and imaging environment. At our core, we are a technology company – deeply committed to building our own R&D capabilities, leveraging emerging technologies and partnerships to bring together a library of intellectual property that can add value to our customer's business. Caring for our communities and creating growth opportunities by investing in talent are woven into our culture. It’s how we care, grow, and win together. Job Description/Responsibilities: We are looking for a highly skilled and strategic Data Architect with deep expertise in the Azure Data ecosystem . This role requires a strong command over Azure Databricks , Azure Data Lake , Azure Data Factory , data warehouse design , SQL optimization , and AI/ML integration . The Data Architect will design and oversee robust, scalable, and secure data architectures to support advanced analytics and machine learning workloads. Qualification: BE/ME/MCA with 10+ Years in IT Experience. Must Have Skills/Skill Requirement: Define and drive the overall Azure-based data architecture strategy aligned with enterprise goals. Architect and implement scalable data pipelines, data lakes, and data warehouses using Azure Data Lake, ADF, and Azure SQL/Synapse. Provide technical leadership on Azure Databricks (Spark, Delta Lake, Notebooks, MLflow etc.) for large-scale data processing and advanced analytics use cases. Integrate AI/ML models into data pipelines and support end-to-end ML lifecycle (training, deployment, monitoring). Collaborate with cross-functional teams including data scientists, DevOps engineers, and business analysts. Evaluate and recommend tools, platforms, and design patterns for data and ML infrastructure. Mentor data engineers and junior architects on best practices and architectural standards. Strong experience with data modeling, ETL/ELT frameworks, and data warehousing concepts. Proficient in SQL, Python, PySpark. Solid understanding of AI/ML workflows and tools. Exposure on Azure DevOps. Excellent communication and stakeholder management skills. How to Apply ? Are you an innovator? Here is your chance to make your mark with a global technology leader. Apply now! Global Privacy Notice Lexmark is committed to appropriately protecting and managing any personal information you share with us. Click here to view Lexmark's Privacy Notice.

Job Title: Senior AI Cloud Operations Engineer Seniority: 4-5 OffShore Profile Summary: We're looking for a Senior AI Cloud Operations Engineer to start building a new for AI Cloud Operations team, starting with this strategic position. We are searching for an experienced Senior AI Cloud Operations Engineer with deep expertise in AI technologies to lead our cloud-based AI infrastructure management. This role is integral to ensuring our AI systems scalability, reliability, and performance, enabling us to deliver cutting-edge solutions. The ideal candidate will have a robust understanding of machine learning frameworks, cloud services architecture, and operations management. Key Responsibilities: Cloud Architecture Design: Design, architect, and manage scalable cloud infrastructure tailored for AI workloads, leveraging platforms like AWS, Azure, or Google Cloud. System Monitoring and Optimization: Implement comprehensive monitoring solutions to ensure high availability and swift performance, utilizing tools like Prometheus, Grafana, or CloudWatch. Collaboration and Model Deployment: Work closely with data scientists to operationalize AI models, ensuring seamless integration with existing systems and workflows. Familiarity with tools such as MLflow or TensorFlow Serving can be beneficial. Automation and Orchestration: Develop automated deployment pipelines using orchestration tools like Kubernetes and Terraform to streamline operations and reduce manual interventions. Security and Compliance: Ensure that all cloud operations adhere to security best practices and compliance standards, including data privacy regulations like GDPR or HIPAA. Documentation and Reporting: Create and maintain detailed documentation of cloud configurations, procedures, and operational metrics to foster transparency and continuous improvement. Performance Tuning: Conduct regular performance assessments and implement strategies to optimize cloud resource utilization and reduce costs without compromising system effectiveness. Issue Resolution: Rapidly identify, diagnose, and resolve technical issues, minimizing downtime and ensuring maximum uptime. Qualifications: Educational Background: Bachelor's degree in Computer Science, Engineering, or a related field. Master's degree preferred. Professional Experience: 5+ years of extensive experience in cloud operations, particularly within AI environments. Demonstrated expertise in deploying and managing complex AI systems in cloud settings . Technical Expertise: Deep knowledge of cloud platforms (AWS, Azure, Google Cloud) including their AI-specific services such as AWS SageMaker or Google AI Platform. AI/ML Proficiency: In-depth understanding of AI/ML frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn, along with experience in ML model lifecycle management. Infrastructure as Code: Proficiency in infrastructure-as-code tools such as Terraform and AWS CloudFormation to automate and manage cloud deployment processes. Containerization and Microservices: Expertise in managing containerized applications using Docker and orchestrating services with Kubernetes. Soft Skills: Strong analytical, problem-solving, and communication skills, with the ability to work effectively both independently and in collaboration with cross-functional teams. Preferred Qualifications Advanced certifications in cloud services, such as AWS Certified Solutions Architect or Google Cloud Professional Data Engineer. Experience in advanced AI techniques such as deep learning or reinforcement learning. Knowledge of emerging AI technologies and trends to drive innovation within existing infrastructure. List of Used Tools: Cloud Provider: Azure, AWS or Google. Performance & monitor: Prometheus, Grafana, or CloudWatch. Collaboration and Model Deployment: MLflow or TensorFlow Serving Automation and Orchestration: Kubernetes and Terraform Security and Compliance: Data privacy regulations like GDPR or HIPAA. Job Title: Senior AI Cloud Operations Engineer Seniority: 4-5 OffShore Profile Summary: We're looking for a Senior AI Cloud Operations Engineer to start building a new for AI Cloud Operations team, starting with this strategic position. We are searching for an experienced Senior AI Cloud Operations Engineer with deep expertise in AI technologies to lead our cloud-based AI infrastructure management. This role is integral to ensuring our AI systems scalability, reliability, and performance, enabling us to deliver cutting-edge solutions. The ideal candidate will have a robust understanding of machine learning frameworks, cloud services architecture, and operations management. Key Responsibilities: Cloud Architecture Design: Design, architect, and manage scalable cloud infrastructure tailored for AI workloads, leveraging platforms like AWS, Azure, or Google Cloud. System Monitoring and Optimization: Implement comprehensive monitoring solutions to ensure high availability and swift performance, utilizing tools like Prometheus, Grafana, or CloudWatch. Collaboration and Model Deployment: Work closely with data scientists to operationalize AI models, ensuring seamless integration with existing systems and workflows. Familiarity with tools such as MLflow or TensorFlow Serving can be beneficial. Automation and Orchestration: Develop automated deployment pipelines using orchestration tools like Kubernetes and Terraform to streamline operations and reduce manual interventions. Security and Compliance: Ensure that all cloud operations adhere to security best practices and compliance standards, including data privacy regulations like GDPR or HIPAA. Documentation and Reporting: Create and maintain detailed documentation of cloud configurations, procedures, and operational metrics to foster transparency and continuous improvement. Performance Tuning: Conduct regular performance assessments and implement strategies to optimize cloud resource utilization and reduce costs without compromising system effectiveness. Issue Resolution: Rapidly identify, diagnose, and resolve technical issues, minimizing downtime and ensuring maximum uptime. Qualifications: Educational Background: Bachelor's degree in Computer Science, Engineering, or a related field. Master's degree preferred. Professional Experience: 5+ years of extensive experience in cloud operations, particularly within AI environments. Demonstrated expertise in deploying and managing complex AI systems in cloud settings . Technical Expertise: Deep knowledge of cloud platforms (AWS, Azure, Google Cloud) including their AI-specific services such as AWS SageMaker or Google AI Platform. AI/ML Proficiency: In-depth understanding of AI/ML frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn, along with experience in ML model lifecycle management. Infrastructure as Code: Proficiency in infrastructure-as-code tools such as Terraform and AWS CloudFormation to automate and manage cloud deployment processes. Containerization and Microservices: Expertise in managing containerized applications using Docker and orchestrating services with Kubernetes. Soft Skills: Strong analytical, problem-solving, and communication skills, with the ability to work effectively both independently and in collaboration with cross-functional teams. Preferred Qualifications Advanced certifications in cloud services, such as AWS Certified Solutions Architect or Google Cloud Professional Data Engineer. Experience in advanced AI techniques such as deep learning or reinforcement learning. Knowledge of emerging AI technologies and trends to drive innovation within existing infrastructure. List of Used Tools: Cloud Provider: Azure, AWS or Google. Performance & monitor: Prometheus, Grafana, or CloudWatch. Collaboration and Model Deployment: MLflow or TensorFlow Serving Automation and Orchestration: Kubernetes and Terraform Security and Compliance: Data privacy regulations like GDPR or HIPAA.