916 Mlflow Jobs - Page 2

Collaborate with product managers and software engineers to integrate AI solutions into our products. Experience with LLMs, NLP, or computer vision. Familiarity with MLOps tools (e.g., MLflow, DVC) and model lifecycle management. Experience with cloud platforms (AWS, Azure, or GCP) and containerization tools (Docker, Kubernetes). Design and implement machine learning models and AI algorithms to solve real-world problems. Build and maintain scalable data pipelines and model deployment infrastructure. Monitor, evaluate, and continuously improve model performance in production. Stay current with the latest AI research and apply relevant findings to our products. Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or a related field. Proficiency in Python and experience with ML frameworks like TensorFlow, PyTorch, or Scikit-learn. Strong understanding of data structures, algorithms, and software engineering principles. Knowledge of vector databases and retrieval-augmented generation (RAG). Exposure to CI/CD pipelines and DevOps practices. Job Types: Full-time, Permanent Pay: From ₹25,000.00 per month Benefits: Health insurance Provident Fund Supplemental Pay: Yearly bonus Work Location: In person

Company Description Betterdata is a leading provider of an AI Programmable Synthetic Data Platform that helps data & AI teams to share data safely and compliantly. By anonymizing sensitive real data into privacy-preserving synthetic data, our platform enables instant and secure data sharing globally while prioritizing data privacy. Visit our job openings at https://tinyurl.com/betterdatajobs. Role Description This is a full-time remote role for an Entry-level / Intern MLOps Engineer at Betterdata. The MLOps Engineer will be responsible for day-to-day tasks involving deploying machine learning models, managing pipelines, monitoring model performance, and ensuring smooth integration of data and ML systems. Key Responsibilities: Deploy and manage Kubernetes clusters and Docker containers for ML workloads Build and maintain automation using Jenkins, Argo Workflows, Argo Events, and Argo CD Write Bash and Python scripts to automate infrastructure and ML pipelines Work across cloud platforms (AWS, Azure, GCP) to configure and manage cloud-native components like: Kubernetes (AKs, EKS, GKE) Storage (e.g., S3, Blob, GCS) Compute (e.g., EC2, Azure VMs, GCE) Networking (e.g., VPC, Load Balancers) IAM and Secrets Management Monitor and troubleshoot infrastructure for ML pipelines Collaborate with the MLOps lead to explore and integrate new tools and practices Qualifications: Bash scripting Docker & Kubernetes Jenkins or similar CI/CD tools (e.g:Github actions) Python scripting One or more cloud platforms (AWS, Azure, GCP) Basic networking concepts Interest or experience in the Argo ecosystem (Workflows, Events, CD) Exposure to MLOps tools like MLflow, Airflow etc Experience deploying ML models or pipelines in cloud/on-premise air gapped environments Degree in Computer Science, Machine Learning, or related field. Exceptional analytical and problem-solving skills. Fast learner with a proactive mindset and eagerness to grow Clear communicator and effective collaborator Why Join Us: Join a team poised to make significant impacts in the synthetic data technology space, where your contributions will shape the future of the field. Real-world exposure to MLOps challenges and solutions. Our start-up environment offers the excitement of innovation and problem-solving, competitive compensation, opportunity to be converted and the chance to challenge and expand your skills at the intersection of data privacy and utility.

About Us: Systango Technologies Limited (NSE: SYSTANGO) is a digital engineering company that offers enterprise-class IT and product engineering services to different size organizations. At Systango, we have a culture of efficiency - we use the best-in-breed technologies to commit quality at speed and world-class support to address critical business challenges. We leverage Gen AI, AI/Machine Learning and Blockchain to unlock the next stage of digitalization for traditional businesses. Our handpicked team is adept at web & enterprise development, mobile apps, QA and DevOps. Ulster University, Sila, Cuentas, Youtility, Porsche, MGM Grand, Deloitte, Grindr, and Tawk.to are some of the top clients that have entrusted us to enhance their digital capabilities and build disruptive innovations. We believe in making the impossible, Possible and we do it literally. About the Role: We are looking for a highly skilled and experienced AI/ML Lead with deep technical expertise in machine learning, deep learning, and Generative AI. The ideal candidate will have a strong programming foundation in Python and hands-on experience with modern ML/DL frameworks, version control systems, and data pipeline tools. This role requires both individual contribution and leadership in driving AI initiatives, while effectively communicating with cross-functional teams and stakeholders. Key Responsibilities: Lead the design, development, and deployment of ML/DL models for real-world applications. Apply advanced techniques such as ensemble learning, transformers, GANs, LSTMs , and reinforcement learning . Work across diverse domains like NLP, computer vision , or recommendation systems based on project needs. Build scalable APIs and services using Flask , Django , or FastAPI . Collaborate with data engineering teams to ensure data readiness for model training and evaluation. Evaluate and fine-tune models using techniques like cross-validation, hyperparameter tuning , and performance metrics. Drive GenAI adoption by leveraging LLM APIs for inference and contribute to LLM training and deployment (if applicable). Document solution architecture, workflows, and technical implementation details clearly. Mentor junior engineers and collaborate with product managers, data scientists, and other technical teams. Required Skills & Qualifications: 6–9 years of hands-on experience in AI/ML and deep learning. Strong programming skills in Python and good understanding of object-oriented programming . Deep knowledge of neural networks including GANs, transformers, LSTMs , etc. Proficient in scikit-learn, pandas, NumPy , and frameworks like TensorFlow-Keras or PyTorch . Experience with version control tools such as Git and GitHub . Solid skills in data visualization tools like Matplotlib , Seaborn , or similar. Familiarity with SQL and NoSQL databases . Experience building RESTful APIs using Django , Flask , or FastAPI . Hands-on experience with GenAI models, especially using LLM APIs for inference. Good understanding of model evaluation techniques and performance metrics. Outstanding verbal and written communication skills, with the ability to clearly articulate complex technical topics. Preferred Qualifications: Exposure to LLM training and deployment workflows. Experience with Big Data technologies such as Hadoop, Spark , etc. Certifications in AI/ML or cloud-based AI platforms (AWS, GCP, Azure). Experience in MLOps tools like MLflow, Kubeflow, or Weights & Biases (nice to have). Why Join Us? Be part of cutting-edge AI and GenAI product development. Work in a collaborative and innovation-driven environment. Lead high-impact projects with global exposure. Excellent growth opportunities and performance-driven culture.

Greetings from Fresh Gravity About Fresh Gravity: Founded in 2015, Fresh Gravity helps businesses make data-driven decisions. We are driven by data and its potential as an asset to drive business growth and efficiency. Our consultants are passionate innovators who solve clients' business problems by applying best-in-class data and analytics solutions. We provide a range of consulting and systems integration services and solutions to our clients in the areas of Data Management, Analytics and Machine Learning, and Artificial Intelligence. In the last 10 years, we have put together an exceptional team and have delivered 200+ projects for over 80 clients ranging from startups to several fortune 500 companies. We are on a mission to solve some of the most complex business problems for our clients using some of the most exciting new technologies, providing the best of learning opportunities for our team. We are focused and intentional about building a strong corporate culture in which individuals feel valued, supported, and cared for. We foster an environment where creativity thrives, paving the way for groundbreaking solutions and personal growth. Our open, collaborative, and empowering work culture is the main reason for our growth and success. To know more about our culture and employee benefits, visit out website https://www.freshgravity.com/employee-benefits/ . We promise rich opportunities for you to succeed, to shine, to exceed even your own expectations. We are data driven. We are passionate. We are innovators. We are Fresh Gravity. Requirements Strong foundation in machine learning theory and the full model development lifecycle Proficient in Python and libraries: scikit-learn, pandas, numpy, transformers. Hands-on with TensorFlow and PyTorch for deep learning Experience using MLflow for tracking, versioning, and deployment. Working knowledge of ETL, SQL, and data modeling Practical experience with Azure services, including: Azure Databricks Azure Machine Learning / MLflow Azure Data Factory Azure Data Lake / Blob Storage Azure OpenAI Familiar with MLOps, version control, and pipeline automation Strong communication skills and experience in Agile, cross-functional teams Benefits In addition to a competitive package, we promise rich opportunities for you to succeed, to shine, to exceed even your own expectations. In keeping with Fresh Gravity's challenger ethos, we have developed the 5Dimensions (5D) benefits program. This program recognizes the multiple dimensions within each of us and seeks to provide opportunities for deep development across these dimensions. Enrich Myself; Enhance My Client; Build my Company, Nurture My Family; and Better Humanity.

About the Role We’re looking for top-tier AI/ML Engineers with 6+ years of experience to join our fast-paced and innovative team. If you thrive at the intersection of GenAI, Machine Learning, MLOps, and application development, we want to hear from you. You’ll have the opportunity to work on high-impact GenAI applications and build scalable systems that solve real business problems. Key Responsibilities Design, develop, and deploy GenAI applications using techniques like RAG (Retrieval Augmented Generation), prompt engineering, model evaluation, and LLM integration. Architect and build production-grade Python applications using frameworks such as FastAPI or Flask. Implement gRPC services, event-driven systems (Kafka, PubSub), and CI/CD pipelines for scalable deployment. Collaborate with cross-functional teams to frame business problems as ML use-cases — regression, classification, ranking, forecasting, and anomaly detection. Own end-to-end ML pipeline development: data preprocessing, feature engineering, model training/inference, deployment, and monitoring. Work with tools such as Airflow, Dagster, SageMaker, and MLflow to operationalize and orchestrate pipelines. Ensure model evaluation, A/B testing, and hyperparameter tuning is done rigorously for production systems. Must-Have Skills Hands-on experience with GenAI/LLM-based applications – RAG, Evals, vector stores, embeddings. Strong backend engineering using Python, FastAPI/Flask, gRPC, and event-driven architectures. Experience with CI/CD, infrastructure, containerization, and cloud deployment (AWS, GCP, or Azure). Proficient in ML best practices: feature selection, hyperparameter tuning, A/B testing, model explainability. Proven experience in batch data pipelines and training/inference orchestration. Familiarity with tools like Airflow/Dagster, SageMaker, and data pipeline architecture.

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 i 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  #mlops #awssagemaker #mlflow #python #aws #docker #immediatejoiner #remotemode #ai/mlsolutions

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by diversity and inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health equity on a global scale. Join us to start Caring. Connecting. Growing together Primary Responsibilities Machine Learning Model Development: Assist in designing and developing machine learning models to address business challenges Perform data preprocessing and feature engineering Support model selection and initial optimization Model Deployment and Monitoring: Assist in deploying machine learning models into production environments Monitor model performance and suggest updates and improvements Ensure models are reliable and maintainable Data Science and Data Engineering: Conduct exploratory data analysis and visualize data insights Help develop and maintain data pipelines for efficient data processing Work with data engineers to ensure data quality and integrity Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so Required Qualifications Bachelor's degree in Computer Science, Data Science, Engineering, or a related field 3+ years of experience in AI/ML engineering, data science, or a related role Experience in developing and deploying machine learning models Experience with natural language processing (NLP) and large language models (LLMs) Experience in Data Manipulation and Analysis (e.g., Pandas, NumPy, Matplotlib, Jupyter Notebooks, Databricks, AI Studio) Proficiency in data manipulation and analysis using SQL/NoSQL, Pandas, or similar tools/technologies Familiarity with cloud platforms (e.g., AWS, Azure, GCP) for model deployment Solid problem-solving skills and attention to detail Proven good communication skills Knowledge of big data technologies (e.g., Hadoop, Spark, Hive, Kafka) Solid programming skills in Python, R, Spark/PySpark, Scala, SQL Familiarity with Machine Learning Frameworks and Libraries (e.g., PyTorch, scikit-learn, TensorFlow, MLflow, Keras, XGBoost) Basic understanding of data engineering, ETL processes, and data warehousing Knowledge of visualization tools (e.g., Tableau, Power BI) At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone - of every race, gender, sexuality, age, location and income - deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.

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? Join Mantra Softech as a Senior AI Engineer and help define the future of smart living by designing embedded AI agents , natural language interfaces , and predictive intelligence for next-generation smart devices . From LLMs to edge-deployed vision and sensor analytics, your work will power real-time decisions and intuitive user experiences - all while pushing the boundaries of machine learning innovation. About Us - Mantra Softech Founded in 2006, Mantra Softech is a global leader in high-tech hardware innovation, specializing in biometric and RFID-based solutions. As we expand into the Smart Home ecosystem , we are developing a new portfolio of IoT devices that deliver seamless, secure, and intelligent living experiences. We are building a design-led product team, and this is your opportunity to help shape the identity of a next-gen connected home. 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. As a Senior AI Engineer, You Will i. Drive research initiatives and proof-of-concepts that push the state of the art in generative AI and large-scale machine learning for home-automation projects. ii. Develop AI agents that can interpret, plan, and act autonomously in response to multi-modal inputs iii. Design and implement high-throughput, low-latency AI/ML pipelines and to operate at global scale. iv. 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 . v. Develop and optimize AI models for deployment on embedded hardware. vi. Prototype novel generative AI solutions, integrate advancements into production, and collaborate with research partners. vii. Integrate real-time streaming data (video/audio/sensor) into analytics pipelines and AI workflows. viii. Develop MLOps pipelines : versioning, continuous training, deployment, and monitoring of models. ix. Collaborate on cloud infrastructure (AWS) for scalable backend and edge-cloud sync. Required Skills i. Solid foundation and expertise in developing and deploying statistical ML models ii. Experience with ML frameworks like Scikit-learn, PyTorch, TensorFlow,OpenCV etc. iii. Hands-on experience with real-life signal/data processing (audio, sensor data etc.) is a must iv. Understanding of MLOps tools and lifecycle (e.g., MLflow, DVC, monitoring tools) v. Strong proficiency in Python and/or C/C++ vi. Experience in building multi-modal AI systems (combining text, audio, sensor, vision inputs) vii. Familiarity with voice activity detection (VAD), wake-word detection, and speech-to-command pipelines viii. Hands-on experience with time-series analysis and forecasting models for predictive maintenance ix. Experience with GenAI, prompt engineering and LLMs along with APIs x. Experience with containerization (Docker) and deploying models via microservices architecture xi. Exposure to model quantization and embedded deployment. xii. Strong understanding of data annotation, synthetic data generation, and active learning workflows. Knowledge of code version management like Bit-bucket. xiii. Strong grasp of SQL : writing optimized queries, working with relational schemas, and integrating SQL into ML pipelines xiv. Exposure to NoSQL databases (e.g., MongoDB, Redis) for high-speed or unstructured data applications xv. Knowledge of AI safety, model robustness, and explainability techniques for production-grade systems Preferred Skills i. Experience with LangChain, LlamaIndex, or custom AI agent frameworks ii. Knowledge of digital twins, condition monitoring, or industrial telemetry iii. Exposure to event-driven edge/cloud orchestration Qualifications : Master's degree in relevant or related field of AI/ML from Tier-I/II institute with at least 3-4 years of experience (ref:hirist.tech)

L2/L3 Gen AI Data Scientist Job Requirements Conduct research and analyze state-of-the-art Gen AI techniques to improve prompt generation models and algorithms. Should be able to utilize LLM open-source models and perform hyper-parameter tuning to configure prompts as per business needs. Develop and optimize high-quality prompts for applications. Conduct experiments, analyze data, and provide insights to improve the performance and effectiveness of prompt generation models. Beyond the foundational skills in problem-solving, Python coding, and the ability to navigate through challenges, this role requires expertise in deploying models into production Leadership skills are important. As Senior Data Scientist, you will review the work of junior team members to ensure top-notch quality and provide mentorship as and where needed Advanced understanding of statistical analysis and experienced in developing machine learning models Preferred experience in Insurance domain Skillset Required Experience in creating prompts with OpenAI and Anthropic models 6 - 8 years of experience as a NLP and Python developer and hands-on experience in prompt engineering Fluency with advanced Machine learning algorithms, Excel, Relational database (SQL/PLSQL) Data gathering, research and analytical abilities to develop insightful conclusions and generate solutions Experience on AWS services e.g. EC2, VPC, S3, ELB, RDS, Cloud Watch, Cloud Front, etc. is a plus Familiarity with Databricks and MLFlow is desired Good to have working knowledge of GitHub and Jira

About ValGenesis ValGenesis is a leading digital validation platform provider for life sciences companies. ValGenesis suite of products are used by 30 of the top 50 global pharmaceutical and biotech companies to achieve digital transformation, total compliance and manufacturing excellence/intelligence across their product lifecycle. Learn more about working for ValGenesis, the de facto standard for paperless validation in Life Sciences: https://www.youtube.com/watch?v=tASq7Ld0JsQ About The Role: We are seeking a highly skilled Senior AI/ML Engineer to join our dynamic team to build the next gen applications for our global customers. If you are a technology enthusiast and highly passionate, we are eager to discuss with you about the potential role. Responsibilities: Implement, and deploy Machine Learning solutions to solve complex problems and deliver real business value, i.e. revenue, engagement, and customer satisfaction. Collaborate with data product managers, software engineers and SMEs to identify AI/ML opportunities for improving process efficiency. Develop production-grade ML models to enhance customer experience, content recommendation, content generation, and predictive analysis. Monitor and improve model performance via data enhancement, feature engineering, experimentation and online/offline evaluation. Stay up to date with the latest in machine learning and artificial intelligence and influence AI/ML for the Life science industry. Responsibilities 4 - 8 years of experience in AI/ML engineering, with a track record of handling increasingly complex projects. Strong programming skills in Python, Rust. Experience with Pandas, NumPy, SciPy, OpenCV (for image processing) Experience with ML frameworks, such as scikit-learn, Tensorflow, PyTorch. Experience with GenAI tools, such as Langchain, LlamaIndex, and open-source Vector DBs. Experience with one or more Graph DBs - Neo4J, ArangoDB Experience with MLOps platforms, such as Kubeflow or MLFlow. Expertise in one or more of the following AI/ML domains: Causal AI, Reinforcement Learning, Generative AI, NLP, Dimension Reduction, Computer Vision, Sequential Models. Expertise in building, deploying, measuring, and maintaining machine learning models to address real-world problems. Thorough understanding of software product development lifecycle, DevOps (build, continuous integration, deployment tools) and best practices. Excellent written and verbal communication skills and interpersonal skills. Advanced degree in Computer Science, Machine Learning or related field. We’re on a Mission In 2005, we disrupted the life sciences industry by introducing the world’s first digital validation lifecycle management system. ValGenesis VLMS® revolutionized compliance-based corporate validation activities and has remained the industry standard. Today, we continue to push the boundaries of innovation ― enhancing and expanding our portfolio beyond validation with an end-to-end digital transformation platform. We combine our purpose-built systems with world-class consulting services to help every facet of GxP meet evolving regulations and quality expectations. The Team You’ll Join Our customers’ success is our success. We keep the customer experience centered in our decisions, from product to marketing to sales to services to support. Life sciences companies exist to improve humanity’s quality of life, and we honor that mission. We work together. We communicate openly, support each other without reservation, and never hesitate to wear multiple hats to get the job done. We think big. Innovation is the heart of ValGenesis. That spirit drives product development as well as personal growth. We never stop aiming upward. We’re in it to win it. We’re on a path to becoming the number one intelligent validation platform in the market, and we won’t settle for anything less than being a market leader. How We Work Our Chennai, Hyderabad and Bangalore offices are onsite, 5 days per week. We believe that in-person interaction and collaboration fosters creativity, and a sense of community, and is critical to our future success as a company. ValGenesis is an equal-opportunity employer that makes employment decisions on the basis of merit. Our goal is to have the best-qualified people in every job. All qualified applicants will receive consideration for employment without regard to race, religion, sex, sexual orientation, gender identity, national origin, disability, or any other characteristics protected by local law.

About ValGenesis ValGenesis is a leading digital validation platform provider for life sciences companies. ValGenesis suite of products are used by 30 of the top 50 global pharmaceutical and biotech companies to achieve digital transformation, total compliance and manufacturing excellence/intelligence across their product lifecycle. Learn more about working for ValGenesis, the de facto standard for paperless validation in Life Sciences: https://www.youtube.com/watch?v=tASq7Ld0JsQ About The Role We are seeking an entry level AI/ML Engineer to join our dynamic team to build the next gen applications for our global customers. If you are a technology enthusiast and highly passionate, we are eager to discuss with you about the potential role. Responsibilities Assist in developing AI-driven solutions using LLMs and RAG (Retrieval-Augmented Generation). Integrating APIs like OpenAI or LLama. Support the design and testing of AI-enhanced workflows. Implement database interactions (MySQL or PostgreSQL for structured data). Write and optimize Python/ Node.js scripts for the applications. Assist in developing production-grade ML models to enhance customer experience, content recommendation, content generation. Monitor and improve model performance via data enhancement, feature engineering, experimentation and online/offline evaluation. Stay up to date with the latest in machine learning and artificial intelligence and influence AI/ML for the Life science industry. Requirements 1 - 3 years of experience in AI/ML engineering. Strong programming skills in Python (FastAPI, Flask) or Node.js . Exposure to NLP, LLMs, AI APIs (ChatGPT, Perplexity.ai , LangChain, LlamaIndex). Familiarity with RESTful APIs and Graph Databases (Neo4j, ArangoDB). Basic understanding of cloud platforms (AWS, Azure, GCP). Passion for AI, NLP, and chatbot development. Familiarity with MLOps platforms, such as Kubeflow or MLFlow. Familiarity with one or more of the following AI/ML domains: Causal AI, Reinforcement Learning, Generative AI, NLP, Dimension Reduction, Computer Vision, Sequential Models. Bonus: Knowledge of UI frameworks (React, Next.js ). Good to have – Qdrant or equivalent vector databases. Excellent written and verbal communication skills and interpersonal skills. Advanced degree in Computer Science, Machine Learning or related field. We’re on a Mission In 2005, we disrupted the life sciences industry by introducing the world’s first digital validation lifecycle management system. ValGenesis VLMS® revolutionized compliance-based corporate validation activities and has remained the industry standard. Today, we continue to push the boundaries of innovation ― enhancing and expanding our portfolio beyond validation with an end-to-end digital transformation platform. We combine our purpose-built systems with world-class consulting services to help every facet of GxP meet evolving regulations and quality expectations. The Team You’ll Join Our customers’ success is our success. We keep the customer experience centered in our decisions, from product to marketing to sales to services to support. Life sciences companies exist to improve humanity’s quality of life, and we honor that mission. We work together. We communicate openly, support each other without reservation, and never hesitate to wear multiple hats to get the job done. We think big. Innovation is the heart of ValGenesis. That spirit drives product development as well as personal growth. We never stop aiming upward. We’re in it to win it. We’re on a path to becoming the number one intelligent validation platform in the market, and we won’t settle for anything less than being a market leader. How We Work Our Chennai, Hyderabad and Bangalore offices are onsite, 5 days per week. We believe that in-person interaction and collaboration fosters creativity, and a sense of community, and is critical to our future success as a company. ValGenesis is an equal-opportunity employer that makes employment decisions on the basis of merit. Our goal is to have the best-qualified people in every job. All qualified applicants will receive consideration for employment without regard to race, religion, sex, sexual orientation, gender identity, national origin, disability, or any other characteristics protected by local law.

We are looking for experienced Data Science Consultants to design, develop, and deliver impactful analytics solutions using large, complex, structured, and unstructured datasets (including big data). You will help clients make better, data-driven decisions by applying advanced data science techniques, optimization, and machine learning solutions. What You Will Do: Design, develop, and apply optimization techniques on large and complex datasets to solve real-world problems. Work closely with engineering teams to deploy scalable, efficient, and statistically effective solutions. Lead development of data science capabilities, reusable assets, and offerings to advance analytic capabilities at scale. Engage with clients and internal stakeholders to present and communicate analytical findings clearly. Research and evaluate new datasets, tools, and technologies to enhance analytics platforms. Develop accelerators, prototypes, and reusable frameworks to create efficiency and scalability. Contribute to thought leadership through research papers, presentations, and publications. What You Will Bring: PhD, Master's, or Bachelor's degree in Computer Science, Data Science, Statistics, Applied Mathematics, or related fields (or equivalent experience). 6 to 9 years of relevant industry experience in Data Science, AI/ML, or Applied Analytics. Strong research background in machine learning, deep learning, or statistical modeling. Proven track record of publications in top-tier ML/AI journals is preferred. Solid understanding of optimization techniques, including linear programming, convex optimization, and non-linear programming. Experience in data science algorithms including supervised learning, unsupervised learning, reinforcement learning, simulation modeling, and recommender systems. Hands-on programming experience in Python, R, or similar languages. Familiarity with modern data science and ML tools/platforms (e.g., TensorFlow, PyTorch, Scikit-learn, Spark, MLFlow, Databricks). Experience managing teams and mentoring junior data scientists. Agile project planning and project management experience (preferred). Strong oral and written communication skills to engage both technical and non-technical audiences. Critical thinking, attention to detail, and strong problem-solving mindset. High motivation, professional work ethic, and ability to work independently or in teams.

Key Responsibilities Monitor and maintain health of production AI models (GenAI and traditional ML). Troubleshoot data/model/infra issues across model pipelines, APIs, embeddings, and prompt systems. Collaborate with Engineering and Data Science teams to deploy new versions and manage rollback if needed. Implement automated logging, alerting, and retraining pipelines. Handle prompt performance drift, input/output anomalies, latency issues, and quality regressions. Analyze feedback and real-world performance to propose model or prompt enhancements. Conduct A/B testing, manage baseline versioning and monitor model outputs over time. Document runbooks, RCA reports, model lineage and operational dashboards. Support GenAI adoption by assisting in evaluations, hallucination detection, and prompt optimization. Must-have Skills 1+ year of experience in Data Science, ML, or MLOps. Good grasp of ML lifecycle, model versioning, and basic monitoring principles. Strong Python skills with exposure to ML frameworks (scikit-learn, pandas, etc.). Basic familiarity with LLMs and interest in GenAI (OpenAI, Claude, etc.). Exposure to AWS/GCP/Azure or any MLOps tooling. Comfortable reading logs, parsing metrics, and triaging issues across the stack. Eagerness to work in a production support environment with proactive ownership. Nice-to-Have Skills Prompt engineering knowledge (system prompts, temperature, tokens, etc.). Hands-on with vector stores, embedding models, or LangChain/LlamaIndex. Experience with tools like MLflow, Prometheus, Grafana, Datadog, or equivalent. Basic understanding of retrieval pipelines or RAG architectures. Familiarity with CI/CD and containerization (Docker, GitHub Actions). Ideal Candidate Profile A strong starter who wants to go beyond notebooks and see AI in action. Obsessed with observability, explainability, and zero-downtime AI. Wants to build a foundation in GenAI while leveraging their traditional ML skills. A great communicator who enjoys cross-functional collaboration.

Job Description We are looking for experienced Data Science Consultants to design, develop, and deliver impactful analytics solutions using large, complex, structured, and unstructured datasets (including big data). You will help clients make better, data-driven decisions by applying advanced data science techniques, optimization, and machine learning solutions. What You Will Do: Design, develop, and apply optimization techniques on large and complex datasets to solve real-world problems. Work closely with engineering teams to deploy scalable, efficient, and statistically effective solutions. Lead development of data science capabilities, reusable assets, and offerings to advance analytic capabilities at scale. Engage with clients and internal stakeholders to present and communicate analytical findings clearly. Research and evaluate new datasets, tools, and technologies to enhance analytics platforms. Develop accelerators, prototypes, and reusable frameworks to create efficiency and scalability. Contribute to thought leadership through research papers, presentations, and publications. What You Will Bring: PhD, Master's, or Bachelor's degree in Computer Science, Data Science, Statistics, Applied Mathematics, or related fields (or equivalent experience). 6 to 9 years of relevant industry experience in Data Science, AI/ML, or Applied Analytics. Strong research background in machine learning, deep learning, or statistical modeling. Proven track record of publications in top-tier ML/AI journals is preferred. Solid understanding of optimization techniques, including linear programming, convex optimization, and non-linear programming. Experience in data science algorithms including supervised learning, unsupervised learning, reinforcement learning, simulation modeling, and recommender systems. Hands-on programming experience in Python, R, or similar languages. Familiarity with modern data science and ML tools/platforms (e.g., TensorFlow, PyTorch, Scikit-learn, Spark, MLFlow, Databricks). Experience managing teams and mentoring junior data scientists. Agile project planning and project management experience (preferred). Strong oral and written communication skills to engage both technical and non-technical audiences. Critical thinking, attention to detail, and strong problem-solving mindset. High motivation, professional work ethic, and ability to work independently or in teams.

Job Description We are looking for experienced Data Science Consultants to design, develop, and deliver impactful analytics solutions using large, complex, structured, and unstructured datasets (including big data). You will help clients make better, data-driven decisions by applying advanced data science techniques, optimization, and machine learning solutions. What You Will Do: Design, develop, and apply optimization techniques on large and complex datasets to solve real-world problems. Work closely with engineering teams to deploy scalable, efficient, and statistically effective solutions. Lead development of data science capabilities, reusable assets, and offerings to advance analytic capabilities at scale. Engage with clients and internal stakeholders to present and communicate analytical findings clearly. Research and evaluate new datasets, tools, and technologies to enhance analytics platforms. Develop accelerators, prototypes, and reusable frameworks to create efficiency and scalability. Contribute to thought leadership through research papers, presentations, and publications. What You Will Bring: PhD, Master's, or Bachelor's degree in Computer Science, Data Science, Statistics, Applied Mathematics, or related fields (or equivalent experience). 6 to 9 years of relevant industry experience in Data Science, AI/ML, or Applied Analytics. Strong research background in machine learning, deep learning, or statistical modeling. Proven track record of publications in top-tier ML/AI journals is preferred. Solid understanding of optimization techniques, including linear programming, convex optimization, and non-linear programming. Experience in data science algorithms including supervised learning, unsupervised learning, reinforcement learning, simulation modeling, and recommender systems. Hands-on programming experience in Python, R, or similar languages. Familiarity with modern data science and ML tools/platforms (e.g., TensorFlow, PyTorch, Scikit-learn, Spark, MLFlow, Databricks). Experience managing teams and mentoring junior data scientists. Agile project planning and project management experience (preferred). Strong oral and written communication skills to engage both technical and non-technical audiences. Critical thinking, attention to detail, and strong problem-solving mindset. High motivation, professional work ethic, and ability to work independently or in teams.

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. JobCategory:BigData

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.