98 Ml Pipelines Jobs - Page 2

You will be joining a company that specializes in Identity and Access Management (IAM) and Customer Identity and Access Management (CIAM), offering advanced solutions to enhance security for your workforce, customers, and partners. The company also provides cutting-edge security solutions for various popular CMS and project management platforms such as Atlassian, WordPress, Joomla, Drupal, Shopify, BigCommerce, and Magento. The solutions offered are precise, effective, and focused on improving overall security measures. As an AI/ML Engineer with our team, you will play a crucial role in developing innovative AI-powered products and solutions. The ideal candidate for this position should possess a minimum of 10 years of hands-on experience in creating and implementing advanced AI and ML models and related software systems. This is a full-time employee position based in Baner, Pune. Your responsibilities will include developing machine learning and deep learning models and algorithms to address complex business challenges, enhance processes, and improve product functionality. You will work on deploying personalized large language models (LLMs), developing systems for document parsing, named entity recognition (NER), retrieval-augmented generation (RAG), and chatbots, as well as building robust data and ML pipelines for production scalability and performance. Additionally, you will optimize machine learning models for better performance, scalability, and accuracy using techniques like hyperparameter tuning and model optimization. It is crucial to write high-quality, production-ready code using frameworks such as PyTorch or TensorFlow and stay updated on the latest advancements in AI/ML technologies and tools. To qualify for this role, you should hold a Bachelor's or Master's Degree in Computer Science, Data Science, Computational Linguistics, Natural Processing (NLP), or related fields. You must have extensive experience in developing and deploying machine learning models and algorithms, with proficiency in AI/ML frameworks such as TensorFlow, PyTorch, and scikit-learn. Strong programming skills in Python, Java, or C++ are necessary, along with familiarity with web frameworks like FastAPI, Flask, Django, and agentic AI frameworks such as LangChain, LangGraph, AutoGen, or Crew AI. Knowledge of Data Science and MLOps, including ML/DL, Generative AI, containerization (Docker), and orchestration (Kubernetes) for deployment is essential. Experience with cloud platforms like AWS, Azure, and GCP, as well as AI/ML deployment tools, is highly beneficial. In this role, you will have the opportunity to work with a team of talented individuals in a stable, collaborative, and supportive work environment. You will be constantly exposed to new technologies and have the chance to expand your skills and knowledge in the field of AI/ML. Your communication and collaboration skills will be put to the test as you collaborate with stakeholders to understand business requirements, define project objectives, and deliver AI/ML solutions that meet customer needs and drive business value.,

You will be responsible for designing, building, and deploying scalable NLP/ML models for real-world applications. Your role will involve fine-tuning and optimizing Large Language Models (LLMs) using techniques like LoRA, PEFT, or QLoRA. You will work with transformer-based architectures such as BERT, GPT, LLaMA, and T5, and develop GenAI applications using frameworks like LangChain, Hugging Face, OpenAI API, or RAG (Retrieval-Augmented Generation). Writing clean, efficient, and testable Python code will be a crucial part of your tasks. Collaboration with data scientists, software engineers, and stakeholders to define AI-driven solutions will also be an essential aspect of your work. Additionally, you will evaluate model performance and iterate rapidly based on user feedback and metrics. The ideal candidate should have a minimum of 3 years of experience in Python programming with a strong understanding of ML pipelines. A solid background and experience in NLP, including text preprocessing, embeddings, NER, and sentiment analysis, are required. Proficiency in ML libraries such as scikit-learn, PyTorch, TensorFlow, Hugging Face Transformers, and spaCy is essential. Experience with GenAI concepts, including prompt engineering, LLM fine-tuning, and vector databases like FAISS and ChromaDB, will be beneficial. Strong problem-solving and communication skills are highly valued, along with the ability to learn new tools and work both independently and collaboratively in a fast-paced environment. Attention to detail and accuracy is crucial for this role. Preferred skills include theoretical knowledge or experience in Data Engineering, Data Science, AI, ML, RPA, or related domains. Certification in Business Analysis or Project Management from a recognized institution is a plus. Experience in working with agile methodologies such as Scrum or Kanban is desirable. Additional experience in deep learning and transformer architectures and models, prompt engineering, training LLMs, and GenAI pipeline preparation will be advantageous. Practical experience in integrating LLM models like ChatGPT, Gemini, Claude, etc., with context-aware capabilities using RAG or fine-tuning models is a plus. Knowledge of model evaluation and alignment, as well as metrics to calculate model accuracy, is beneficial. Data curation from sources for RAG preprocessing and development of LLM pipelines is an added advantage. Proficiency in scalable deployment and logging tooling, including skills like Flask, Django, FastAPI, APIs, Docker containerization, and Kubeflow, is preferred. Familiarity with Lang Chain, LlamaIndex, vLLM, HuggingFace Transformers, LoRA, and a basic understanding of cost-to-performance tradeoffs will be beneficial for this role.,

Capgemini Invent Capgemini Invent is the digital innovation, consulting and transformation brand of the Capgemini Group, a global business line that combines market leading expertise in strategy, technology, data science and creative design, to help CxOs envision and build whats next for their businesses. Your Role Edge AI Data Scientists will be responsible for designing, developing, and validating machine learning modelsparticularly in the domain of computer visionfor deployment on edge devices. This role involves working with data from cameras, sensors, and embedded platforms to enable real-time intelligence for applications such as object detection, activity recognition, and visual anomaly detection. The position requires close collaboration with embedded systems and AI engineers to ensure models are lightweight, efficient, and hardware-compatible. Candidate Requirements Education Bachelor"s or Masters degree in Data Science, Computer Science, or a related field. Experience 3+ years of experience in data science or machine learning with a strong focus on computer vision. Experience in developing models for edge deployment and real-time inference. Familiarity with video/image datasets and deep learning model training. Skills Proficiency in Python and libraries such as OpenCV, PyTorch, TensorFlow, and FastAI. Experience with model optimization techniques (quantization, pruning, etc.) for edge devices. Hands-on experience with deployment tools like TensorFlow Lite, ONNX, or OpenVINO. Strong understanding of computer vision techniques (e.g., object detection, segmentation, tracking). Familiarity with edge hardware platforms (e.g., NVIDIA Jetson, ARM Cortex, Google Coral). Experience in processing data from camera feeds or embedded image sensors. Strong problem-solving skills and ability to work collaboratively with cross-functional teams. Your Profile Responsibilities Develop and train computer vision models tailored for constrained edge environments. Analyze camera and sensor data to extract insights and build vision-based ML pipelines. Optimize model architecture and performance for real-time inference on edge hardware. Validate and benchmark model performance on various embedded platforms. Collaborate with embedded engineers to integrate models into real-world hardware setups. Stay up-to-date with state-of-the-art computer vision and Edge AI advancements. Document models, experiments, and deployment configurations. What you will love about working here We recognize the significance of flexible work arrangements to provide support. Be it remote work, or flexible work hours, you will get an environment to maintain healthy work life balance. At the heart of our mission is your career growth. Our array of career growth programs and diverse professions are crafted to support you in exploring a world of opportunities. Equip yourself with valuable certifications in the latest technologies such as Generative AI. About Capgemini Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and iCa sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, cloud and data, combined with its deep industry expertise and partner ecosystem. The Group reported 2023 global revenues of 22.5 billion.

Role: Lead AI/ML Engineer Location: Ambattur, Chennai(Onsite) Fulltime Position Job Summary: We are looking for an AI/ML Engineer to Lead, develop, optimize, and deploy machine learning models for real-world applications. You will work on end-to-end ML pipelines , collaborate with cross-functional teams, and apply AI techniques such as NLP, Computer Vision, and Time-Series Forecasting . This role offers opportunities to work on cutting-edge AI solutions while growing your expertise in model deployment and optimization. Key Responsibilities: Design, build, and optimize machine learning models for various business applications. Develop and maintain ML pipelines , including data preprocessing, feature engineering, and model training. Work with TensorFlow, PyTorch, Scikit-learn, and Keras for model development. Deploy ML models in cloud environments (AWS, Azure, GCP) and work with Docker/Kubernetes for containerization. Perform model evaluation, hyperparameter tuning, and performance optimization . Collaborate with data scientists, engineers, and product teams to deliver AI-driven solutions. Stay up to date with the latest advancements in AI/ML and implement best practices. Write clean, scalable, and well-documented code in Python or R.

As a Data Analyst at our company based in Trivandrum, you will be responsible for analyzing large volumes of log data from NGINX server logs to identify user behavior patterns, anomalies, and security events. Your role will involve interpreting various fields such as IP addresses, geolocation data, user agents, request paths, status codes, and request times to derive meaningful insights. Collaboration with AI engineers is crucial as you will work together to propose relevant features based on log behavior and traffic patterns. Your responsibilities will include validating engineered features, conducting exploratory data analysis, and ensuring the quality and alignment of feature logic with real-world HTTP behavior and use cases. Furthermore, you will be involved in developing data visualizations to represent time-series trends, geo-distributions, and traffic behavior. Your collaboration with the frontend/dashboard team will be essential in defining and testing visual requirements and anomaly indicators for real-time dashboards. In addition to your analytical tasks, you will also be responsible for identifying and addressing gaps, inconsistencies, and errors in raw logs to ensure data quality. Creating documentation that explains observed behavioral patterns, feature assumptions, and traffic insights for knowledge sharing within the ML and security team will also be part of your role. The minimum qualifications for this position include a Bachelor's degree in Computer Science, Information Systems, Data Analytics, Cybersecurity, or a related field, along with at least 2 years of experience in data analysis or analytics roles. Proficiency in SQL, Elasticsearch queries, Python for data analysis, and experience working with web server logs or structured event data are required. Strong analytical thinking skills are essential to break down complex log behavior into patterns and outliers. It would be beneficial if you have familiarity with web security concepts, experience with log analytics platforms, an understanding of feature engineering concepts in ML pipelines, or experience working on anomaly detection or security analytics systems. This is a full-time position with benefits such as health insurance and Provident Fund, with a day shift schedule from Monday to Friday. If you possess the necessary qualifications and experience, we look forward to receiving your application.,

Are you our Type Monotype, named "One of the Most Innovative Companies in Design" by Fast Company, is dedicated to bringing brands to life through type and technology that consumers engage with daily. With a rich legacy spanning centuries, Monotype boasts a library featuring renowned typefaces like Helvetica, Futura, and Times New Roman, among others. Additionally, Monotype offers a pioneering service that enhances access to fonts for creative professionals, facilitating their discovery, licensing, and utilization in today's digital landscape. Collaborating with major global brands and individual creatives, Monotype provides a diverse range of solutions to streamline the design of captivating brand experiences. Monotype Solutions India serves as a strategic center of excellence for Monotype, recognized as a certified Great Place to Work for three consecutive years. The center's rapid growth encompasses various domains such as Product Development, Product Management, Experience Design, User Research, Market Intelligence, AI and Machine Learning research, Innovation, Customer Success, Enterprise Business Solutions, and Sales. Headquartered in the Boston area with a global presence across 4 continents, Monotype stands as the world's leading font company, trusted by the top brands worldwide and acknowledged as One of the Most Innovative Companies in Design by Fast Company. Monotype is a pioneering technology company at the forefront of AI innovation in fonts. We are currently seeking a motivated and curious AI/ML Engineer to join our dynamic team. As an AI/ML Engineer, you will be instrumental in designing and implementing state-of-the-art AI/ML solutions to address real-world challenges. This position is based in the Delhi NCR area. **What you will be doing:** - Designing, developing, and testing AI/ML models using supervised and unsupervised learning techniques. - Preparing and pre-processing data for model training and evaluation. - Collaborating with data scientists and engineers to define project requirements and success metrics. - Deploying and monitoring models in production environments. - Staying updated with the latest advancements in AI/ML research and development. **What we are looking for:** - Bachelor's degree in computer science, mathematics, statistics, or a related field. - Strong grasp of machine learning concepts, algorithms, and techniques. - Knowledge or understanding of deep learning frameworks (TensorFlow, PyTorch) and programming languages (Python, R). - Familiarity with data wrangling and manipulation tools (pandas, NumPy). - Excellent communication and collaboration skills. - A keen interest in continuous learning and exploring new technologies. **Preferred Skills:** - Strong understanding of computer vision, natural language processing, and other AI-related domains. - Knowledge or understanding of generative AI models, particularly Stable Diffusion. - Published research papers or contributions to the AI/ML community are advantageous. - Knowledge or understanding of building and deploying ML pipelines. Monotype is expanding globally, and proficiency in one or more of the following languages (German, Japanese, French, Spanish) is desirable but not mandatory for this role.,

Educational Bachelor of Engineering Service Line Data & Analytics Unit Responsibilities Technical knowledge- has expertise in cloud technologies, specifically MS Azure, and services with hands on coding to – Python Programming - Expert and Experienced - 4 -5 years DevOps Working knowledge with implementation experience - 1 or 2 projects a minimum Hands-On MS Azure Cloud knowledge Understand and take requirements on Operationalization of ML Models from Data Scientist Help team with ML Pipelines from creation to execution List Azure services required for deployment, Azure Data bricks and Azure DevOps Setup Assist team to coding standards (flake8 etc) Guide team to debug on issues with pipeline failures Engage with Business / Stakeholders with status update on progress of development and issue fix Automation, Technology and Process Improvement for the deployed projects Setup Standards related to Coding, Pipelines and Documentation Adhere to KPI / SLA for Pipeline Run, Execution Research on new topics, services and enhancements in Cloud Technologies Additional Responsibilities: Master’s degree in Computer Science Engineering, with Relevant experience in the field of MLOps / Cloud Domain experience in Capital Markets, Banking, Risk and Compliance etc. Exposure to US/ overseas markets is preferred Azure Certified – DP100, AZ/AI900 Domain / Technical / Tools KnowledgeObject oriented programming, coding standards, architecture & design patterns, Config management, Package Management, Logging, documentation Experience in Test Driven Development and experience in using Pytest frameworks, git version control, Rest APIs Azure ML best practices in environment management, run time configurations (Azure ML & Databricks clusters), alerts. Experience designing and implementing ML Systems & pipelines, MLOps practices Exposure to event driven orchestration, Online Model deployment Contribute towards establishing best practices in MLOps Systems development Proficiency with data analysis tools (e.g., SQL, R & Python) High level understanding of database concepts/reporting & Data Science concepts Hands on experience in working with client IT/Business teams in gathering business requirement and converting into requirement for development team Experience in managing client relationship and developing business cases for opportunities Azure AZ-900 Certification with Azure Architecture understanding is a plus Preferred Skills: Technology-Machine Learning-Python

3–5 yrs exp in AI/ML, Python, Azure ML, and model deployment. Build & manage ML pipelines using Azure Data Factory, DevOps, ACI/AKS. Strong in scikit-learn, TensorFlow/PyTorch, MLOps, and large-scale data handling. Location: Mumbai.

Job Title: AWS Engineer Experience: 4 - 8 Years Location: Bengaluru (Hybrid 2- 3 Days Onsite per Week) Employment Type: Full-Time Notice Period: Only Immediate to 15 Days Joiners Preferred Job Description: We are looking for an experienced AWS Engineer to join our dynamic data engineering team. The ideal candidate will have hands-on experience building and maintaining robust, scalable data pipelines and cloud-based architectures on AWS. Key Responsibilities: Design, develop, and maintain scalable data pipelines using AWS services such as Glue, Lambda, S3, Redshift, and EMR Collaborate with data scientists and ML engineers to operationalize machine learning models using AWS SageMaker Implement efficient data transformation and feature engineering workflows Optimize ETL/ELT processes and enforce best practices for data quality and governance Work with structured and unstructured data using Amazon Athena, DynamoDB, RDS, and similar services Build and manage CI/CD pipelines for data and ML workflows using AWS CodePipeline, CodeBuild, and Step Functions Monitor data infrastructure for performance, reliability, and cost-effectiveness Ensure data security and compliance with organizational and regulatory standards Required Skills: Strong experience with AWS data and ML services Solid knowledge of ETL/ELT frameworks and data modeling Proficiency in Python, SQL, and scripting for data engineering Experience with CI/CD and DevOps practices on AWS Good understanding of data governance and compliance standards Excellent collaboration and problem-solving skills

Build robust ML pipelines with AWS SageMaker, integrate models into production, manage workflows via AWS Data Zone, apply CI/CD best practices, contribute to MLOps research, and optimize ML systems for reliability, speed, and cost-efficiency Required Candidate profile Experienced MLOps Engineer with 5+ yrs in software development, AWS & SageMaker expertise, skilled in Python/R/Scala/Spark, production-grade delivery, and a sharp mindset for MLOps research innovation

Job Summary: We are seeking a highly skilled and motivated Machine Learning Engineer with a strong foundation in programming and machine learning, hands-on experience with AWS Machine Learning services (especially SageMaker), and a solid understanding of Data Engineering and MLOps practices. You will be responsible for designing, developing, deploying, and maintaining scalable ML solutions in a cloud-native environment. ________________________________________ Key Responsibilities: Design and implement machine learning models and pipelines using AWS SageMaker and related services. Develop and maintain robust data pipelines for training and inference workflows. Collaborate with data scientists, engineers, and product teams to translate business requirements into ML solutions. Implement MLOps best practices including CI/CD for ML, model versioning, monitoring, and retraining strategies. Optimize model performance and ensure scalability and reliability in production environments. Monitor deployed models for drift, performance degradation, and anomalies. Document processes, architectures, and workflows for reproducibility and compliance. ________________________________________ Required Skills & Qualifications: Strong programming skills in Python and familiarity with ML libraries (e.g., scikit-learn, TensorFlow, PyTorch). Solid understanding of machine learning algorithms, model evaluation, and tuning. Hands-on experience with AWS ML services, especially SageMaker, S3, Lambda, Step Functions, and CloudWatch. Experience with data engineering tools (e.g., Apache Airflow, Spark, Glue) and workflow orchestration. Proficiency in MLOps tools and practices (e.g., MLflow, Kubeflow, CI/CD pipelines, Docker, Kubernetes). Familiarity with monitoring tools and logging frameworks for ML systems. Excellent problem-solving and communication skills.

Role: ML Ops Engineer Onsite Chennai Exp:5-8 Y Immediate/0-15d Required Skills 1.5+ year exp MLOps/DevOps roles with ML 2. Python, ML libraries 3.Docker&Kubernetes. 4.CI/CD-Jenkins, GitLab, 5.Technology-Azure,AWS,GCP Note: TamilNadu Candidate Only

About the Team Our Data Science team is the Avengers to Meeshos S.H.I.E.L.D ???. And why not? We are the ones who assemble during the toughest challenges and devise creative solutions, building intelligent systems for millions of our users looking at a thousand different categories of products. Weve barely scratched the surface, and have amazing challenges in charting the future of commerce for Bharat. Our typical day involves dealing with fraud detection, inventory optimisation, and platform vernacularisation. As Lead Data Scientist, you will navigate uncharted territories with us, discovering new paths to creating solutions for our users.?? You will be at the forefront of interesting challenges and solve unique customer problems in an untapped market. But wait theres more to us. Our team is huge on having a well-rounded personal and professional life. When we aren't nose-deep in data, you will most likely find us belting Summer of 69 at the nearest Karaoke bar, or debating who the best Spider-Man is: Maguire, Garfield, or Holland? You tell us ?? About the Role Love deep data? Does innovative-thinking describe you? Then you may be our next Lead Data Scientist. In this role youll be the Dumbledore to our team of wizards - our junior data scientists. You will be responsible for transforming scattered pieces of information into valuable data that can be used to achieve goals effectively. You will extract and mine critical bits of information and drive insightful discussions that result in app innovations. What you will do Own and deliver solutions across multiple charters by formulating well-scoped problem statements and driving them to execution with measurable impact Mentor a team of data scientists (DS2s and DS3s), helping them with project planning, execution, and on-call issue resolution Design and optimize key user journeys (e.g., Reseller Experience, Search, Fraud Systems) by identifying user intents and behavioral patterns from large-scale data Collaborate with machine learning engineers and big data teams to build scalable ML pipelines and improve inference performance Continuously track and improve model performance using state-of-the-art (SOTA) techniques and libraries Lead experimental design for usability improvements and user growth, leveraging statistical rigor Contribute to system-level thinking by enhancing internal tools, frameworks, and libraries to improve team efficiency and code quality Partner with engineering to ensure data reliability, compliance with security/PII guidelines, and integration of models into production systems Proactively explore new areas of opportunity through research, data mining, and academic collaboration, including publishing and attending top-tier conferences Communicate findings, plans, and results clearly with DS, product, and tech stakeholders, and create technical documentation consumable by both DS and engineering teams Conduct research collaborations with premier colleges and universities Attend conferences and publish research papers What you will need A Bachelor's degree in Computer Science, Data Science, or a related field; a Masters is a plus 6--8 years of experience in data science with a strong track record of building and deploying ML solutions at scale Deep understanding of core ML techniques supervised, unsupervised, and semi-supervised learning along with strong foundations in statistics and linear algebra Exposure to deep learning concepts and architectures (e.g., CNNs, RNNs, Transformers) and their practical applications Proficiency in Python and SQL, with experience in building data pipelines and analytical workflows Hands-on experience with large-scale data processing using Apache Spark, Hadoop/Hive, or cloud platforms such as GCP Strong programming fundamentals and experience writing clean, maintainable, and production-ready code Excellent analytical and problem-solving skills the ability to extract actionable insights from messy and high-volume data Solid grasp of statistical testing, hypothesis validation, and common pitfalls in experimental design Experience designing and interpreting A/B tests, including uplift measurement and segmentation Ability to work closely with product and engineering teams to translate business goals into scalable ML or data solutions Bonus points for: Experience with reinforcement learning or sequence modeling techniques Contributions to ML libraries, internal tools, or research publications

Job Description If you are looking for a career at a dynamic company with a people-first mindset and a deep culture of growth and autonomy, ACV is the right place for you! Competitive compensation packages and learning and development opportunities, ACV has what you need to advance to the next level in your career. We will continue to raise the bar every day by investing in our people and technology to help our customers succeed. We hire people who share our passion, bring innovative ideas to the table, and enjoy a collaborative atmosphere. Who we are: ACV is a technology company that has revolutionized how dealers buy and sell cars online. We are transforming the automotive industry. ACV Auctions Inc. (ACV), has applied innovation and user-designed, data driven applications and solutions. We are building the most trusted and efficient digital marketplace with datasolutions for sourcing, selling and managing used vehicles with transparency and comprehensive insights that were once unimaginable. We are disruptors of theindustry and we want you to join us on our journey. ACVs network of brands includes ACV Auctions, ACV Transportation, ClearCar, MAX Digital and ACV Capital within its Marketplace Products, as well as, True360 and Data Services. ACV Auctions is opening its new India Development Center in Chennai, India, and were looking for talented individuals to join our team. As we expand our platform, were offering a wide range of exciting opportunities across various roles. At ACV, we put people first and believe in the principles of trust and transparency. If you are looking for an opportunity to work with the best minds in the industry and solve unique business and technology problems? Look no further! Join us in shaping the future of the automotive marketplace! At ACV we focus on the Health, Physical, Financial, Social and Emotional Wellness of our Teammates and to support this we offer industry leading benefits and wellness programs. What you will do: ACVs Machine Learning (ML) team is looking to grow its MLOps team. Multiple ACV operations and product teams rely on the ML teams solutions. Current deployments drive opportunities in the marketplace, in operations, and sales, to name a few. As ACV has experienced hyper growth over the past few years, the volume, variety, and velocity of these deployments has grown considerably. Thus, the training, deployment, and monitoring needs of the ML team has grown as weve gained traction. MLOps is a critical function to help ourselves continue to deliver value to our partners and our customers. Successful candidates will demonstrate excellent skill and maturity, be self-motivated as well as team-oriented, and have the ability to support the development and implementation of end-to-end ML-enabled software solutions to meet the needs of their stakeholders. Those who will excel in this role will be those who listen with an ear to the overarching goal, not just the immediate concern that started the query. They will be able to show their recommendations are contextually grounded in an understanding of the practical problem, the data, and theory as well as what product and software solutions are feasible and desirable. The core responsibilities of this role are: Working with fellow machine learning engineers to build, automate, deploy, and monitor ML applications. Developing data pipelines that feed ML models. Deploy new ML models into production. Building REST APIs to serve ML models predictions. Monitoring performance of models in production. Required Qualifications: Graduate education in a computationally intensive domain or equivalent work experience. 5+ years of prior relevant work or lab experience in ML projects/research, and 1+ years as tech lead or major contributor on cross-team projects. Advanced proficiency with Python, SQL etc. Experience with cloud services (AWS / GCP) and kubernetes, docker, CI/CD. Preferred Qualifications: Experience with MLOps-specific tooling like Vertex AI, Ray, Feast, Kubeflow, or ClearML, etc. are a plus. Experience with EDA, including data pipeline building and data visualization. Experience with building ML models.

Role and Responsibilities Design, develop, implement, and maintain AIML products to solve specific business problems Optimize the existing codes using advanced programming skills Execute AIML POC projects Collaborate with various stake holders (Data engineers, Cloud Engineers, Bas) in the practice to deliver optimal outcomes Work on various cloud platforms includes AWS, AZURE and GCP Work on big-data tools (PySpark) Design and develop ML pipelines includes feature engineering, model training & testing, model health monitoring and deployments Create reports, projections, models, and presentations to support business strategy and tactics Exercise independent judgment and decision making on complex issues regarding job duties and related tasks, and work under minimal supervision, use independent judgment requiring analysis of variable factors and determining the best course of action Qualifications and Education Requirements Master's Degree (Data Science/statistics/ Mathematics/Computer Science) + 8years of experience, or equivalent experience with a Bachelors degree Proficiency in programming, preferably Python, R, and SQL (PostgreSQL MySQL/) and NoSQL (MongoDB) Experience of Advanced programming in python/R/Spark includes developing multi-threading and Parallel Processing Experience in designing, developing, implementing and deploying ML products Experience in using mathematics, statistics, modeling, business analysis, and technology to transform high volumes of complex data into advanced analytic solutions Demonstrated experience in AI Implementation and ML modeling problems of diverse scope and complexity Experience in Supervised and Unsupervised ML models training, testing and Validations Experience in developing, maintaining, and collecting structured and unstructured data sets for analysis and reporting Experience in creating reports, projections, models, and presentations to support business Ability to exercise independent judgment and decision making on complex issues regarding job duties and related tasks Ability to works under minimal supervision, using independent judgment Experience of working in agile & CICD environment Preferred Skills PhD in Math/Stat/Computer science/Data Science/Engineering Previous experience in IOT industry Experience in leading/ mentoring Experience in Hadoop Experience in Kafka Streaming.

Role and Responsibilities Design, develop, implement, and maintain AIML products to solve specific business problems Optimize the existing codes using advanced programming skills Execute AIML POC projects Collaborate with various stake holders (Data engineers, Cloud Engineers, Bas) in the practice to deliver optimal outcomes Work on various cloud platforms includes AWS, AZURE and GCP Work on big-data tools (PySpark) Design and develop ML pipelines includes feature engineering, model training & testing, model health monitoring and deployments Create reports, projections, models, and presentations to support business strategy and tactics Exercise independent judgment and decision making on complex issues regarding job duties and related tasks, and work under minimal supervision, use independent judgment requiring analysis of variable factors and determining the best course of action Qualifications and Education Requirements Master's Degree (Data Science/statistics/Mathematics/Computer Science) + 8years of experience, or equivalent experience with a Bachelor s degree Proficiency in programming, preferably Python, R, and SQL (PostgreSQL MySQL/) and NoSQL (MongoDB) Experience of Advanced programming in python/R/Spark includes developing multi-threading and Parallel Processing Experience in designing, developing, implementing and deploying ML products Experience in using mathematics, statistics, modeling, business analysis, and technology to transform high volumes of complex data into advanced analytic solutions Demonstrated experience in AI Implementation and ML modeling problems of diverse scope and complexity Experience in Supervised and Unsupervised ML models training, testing and Validations Experience in developing, maintaining, and collecting structured and unstructured data sets for analysis and reporting Experience in creating reports, projections, models, and presentations to support business Ability to exercise independent judgment and decision making on complex issues regarding job duties and related tasks Ability to works under minimal supervision, using independent judgment Experience of working in agile & CICD environment Preferred Skills PhD in Math/Stat/Computer science/Data Science/Engineering Previous experience in IOT industry Experience in leading/ mentoring Experience in Hadoop Experience in Kafka Streaming

We are looking for a Machine Learning Engineer with expertise in MLOps (Machine Learning Operations) or LLMOps (Large Language Model Operations) to design, deploy, and maintain scalable AI/ML systems. You will work on automating ML workflows, optimizing model deployment, and managing large-scale AI applications, including LLMs (Large Language Models) , ensuring they run efficiently in production. Key Responsibilities: Design and implement end-to-end MLOps pipelines for training, validation, deployment, monitoring, and retraining of ML models. Optimize and fine-tune large language models (LLMs) for various applications, ensuring performance and efficiency. Develop CI/CD pipelines for ML models to automate deployment and monitoring in production. Monitor model performance, detect drift , and implement automated retraining mechanisms. Work with cloud platforms ( AWS, GCP, Azure ) and containerization technologies ( Docker, Kubernetes ) for scalable deployments. Implement best practices in data engineering , feature stores, and model versioning. Collaborate with data scientists, engineers, and product teams to integrate ML models into production applications. Ensure compliance with security, privacy, and ethical AI standards in ML deployments. Optimize inference performance and cost of LLMs using quantization, pruning, and distillation techniques . Deploy LLM-based APIs and services, integrating them with real-time and batch processing pipelines. Key Requirements: Technical Skills: Strong programming skills in Python, with experience in ML frameworks ( TensorFlow, PyTorch, Hugging Face, JAX ). Experience with MLOps tools (MLflow, Kubeflow, Vertex AI, SageMaker, Airflow). Deep understanding of LLM architectures , prompt engineering, and fine-tuning. Hands-on experience with containerization (Docker, Kubernetes) and orchestration tools . Proficiency in cloud services (AWS/GCP/Azure) for ML model training and deployment. Experience with monitoring ML models (Prometheus, Grafana, Evidently AI). Knowledge of feature stores (Feast, Tecton) and data pipelines (Kafka, Apache Beam). Strong background in distributed computing (Spark, Ray, Dask) . Soft Skills: Strong problem-solving and debugging skills. Ability to work in cross-functional teams and communicate complex ML concepts to stakeholders. Passion for staying updated with the latest ML and LLM research & technologies . Preferred Qualifications: Experience with LLM fine-tuning , Reinforcement Learning with Human Feedback ( RLHF ), or LoRA/PEFT techniques . Knowledge of vector databases (FAISS, Pinecone, Weaviate) for retrieval-augmented generation ( RAG ). Familiarity with LangChain, LlamaIndex , and other LLMOps-specific frameworks. Experience deploying LLMs in production (ChatGPT, LLaMA, Falcon, Mistral, Claude, etc.) .

Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote (*Note: This is a requirement for one of Uplers' client - A fast-growing, VC-backed B2B SaaS platform revolutionizing financial planning and analysis for modern finance teams.) What do you need for this opportunity? Must have skills required: async workflows, MLOps, Ray Tune, Data Engineering, MLFlow, Supervised Learning, Time-Series Forecasting, Docker, machine_learning, NLP, Python, SQL A fast-growing, VC-backed B2B SaaS platform revolutionizing financial planning and analysis for modern finance teams. is Looking for: We are a fast-moving startup building AI-driven solutions to the financial planning workflow. Were looking for a versatile Machine Learning Engineer to join our team and take ownership of building, deploying, and scaling intelligent systems that power our core product. Job Description- Full-time Team: Data & ML Engineering Were looking for 5+ years of experience as a Machine Learning or Data Engineer (startup experience is a plus) WHAT YOU WILL DO- Build and optimize machine learning models from regression to time-series forecasting Work with data pipelines and orchestrate training/inference jobs using Ray, Airflow, and Docker Train, tune, and evaluate models using tools like Ray Tune, MLflow, and scikit-learn Design and deploy LLM-powered features and workflows Collaborate closely with product managers to turn ideas into experiments and production-ready solutions Partner with Software and DevOps engineers to build robust ML pipelines and integrate them with the broader platform BASIC SKILLS Proven ability to work creatively and analytically in a problem-solving environment Excellent communication (written and oral) and interpersonal skills Strong understanding of supervised learning and time-series modeling Experience deploying ML models and building automated training/inference pipelines Ability to work cross-functionally in a collaborative and fast-paced environment Comfortable wearing many hats and owning projects end-to-end Write clean, tested, and scalable Python and SQL code Leverage async workflows and cloud-native infrastructure (S3, Docker, etc.) for high-throughput data processing. ADVANCED SKILLS Familiarity with MLOps best practices Prior experience with LLM-based features or production-level NLP Experience with LLMs, vector stores, or prompt engineering Contributions to open-source ML or data tools TECH STACK Languages: Python, SQL Frameworks & Tools: scikit-learn, Prophet, pyts, MLflow, Ray, Ray Tune, Jupyter Infra: Docker, Airflow, S3, asyncio, Pydantic

About the Role: Grade Level (for internal use): 12 The Team As a member of the EDO, Collection Platforms & AI Cognitive Engineering team you will spearhead the design and delivery of robust, scalable ML infrastructure and pipelines that power natural language understanding, data extraction, information retrieval, and data sourcing solutions for S&P Global. You will define AI/ML engineering best practices, mentor fellow engineers and data scientists, and drive production-ready AI products from ideation through deployment. Youll thrive in a (truly) global team that values thoughtful risk-taking and self-initiative. Whats in it for you Be part of a global company and build solutions at enterprise scale Lead and grow a technically strong ML engineering function Collaborate on and solve high-complexity, high-impact problems Shape the engineering roadmap for emerging AI/ML capabilities (including GenAI integrations) Key Responsibilities Architect, develop, and maintain production-ready data acquisition, transformation, and ML pipelines (batch & streaming) Serve as a hands-on lead-writing code, conducting reviews, and troubleshooting to extend and operate our data platforms Apply best practices in data modeling, ETL design, and pipeline orchestration using cloud-native solutions Establish CI/CD and MLOps workflows for model training, validation, deployment, monitoring, and rollback Integrate GenAI components-LLM inference endpoints, embedding stores, prompt services-into broader ML systems Mentor and guide engineers and data scientists; foster a culture of craftsmanship and continuous improvement Collaborate with cross-functional stakeholders (Data Science, Product, IT) to align on requirements, timelines, and SLAs What Were Looking For 8-12 years' professional software engineering experience with a strong MLOps focus Expert in Python and Apache for large-scale data processing Deep experience deploying and operating ML pipelines on AWS or GCP Hands-on proficiency with container/orchestration tooling Solid understanding of the full ML model lifecycle and CI/CD principles Skilled in streaming and batch ETL design (e.g., Airflow, Dataflow) Strong OOP design patterns, Test-Driven Development, and enterprise system architecture Advanced SQL skills (big-data variants a plus) and comfort with Linux/bash toolsets Familiarity with version control (Git, GitHub, or Azure DevOps) and code review processes Excellent problem-solving, debugging, and performance-tuning abilities Ability to communicate technical change clearly to non-technical audiences Nice to have Redis, Celery, SQS and Lambda based event driven pipelines Prior work integrating LLM services (OpenAI, Anthropic, etc.) at scale Experience with Apache Avro and Apache Familiarity with Java and/or .NET Core (C#) Whats In It For You Our Purpose: Progress is not a self-starter. It requires a catalyst to be set in motion. Information, imagination, people, technologythe right combination can unlock possibility and change the world.Our world is in transition and getting more complex by the day. We push past expected observations and seek out new levels of understanding so that we can help companies, governments and individuals make an impact on tomorrow. At S&P Global we transform data into Essential Intelligence, pinpointing risks and opening possibilities. We Accelerate Progress. Our People: Our Values: Integrity, Discovery, Partnership At S&P Global, we focus on Powering Global Markets. Throughout our history, the world's leading organizations have relied on us for the Essential Intelligence they need to make confident decisions about the road ahead. We start with a foundation of integrity in all we do, bring a spirit of discovery to our work, and collaborate in close partnership with each other and our customers to achieve shared goals. Benefits: We take care of you, so you cantake care of business. We care about our people. Thats why we provide everything youand your careerneed to thrive at S&P Global. Health & WellnessHealth care coverage designed for the mind and body. Continuous LearningAccess a wealth of resources to grow your career and learn valuable new skills. Invest in Your FutureSecure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs. Family Friendly PerksIts not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families. Beyond the BasicsFrom retail discounts to referral incentive awardssmall perks can make a big difference. For more information on benefits by country visithttps://spgbenefits.com/benefit-summaries Global Hiring and Opportunity at S&P Global: At S&P Global, we are committed to fostering a connected andengaged workplace where all individuals have access to opportunities based on their skills, experience, and contributions. Our hiring practices emphasize fairness, transparency, and merit, ensuring that we attract and retain top talent. By valuing different perspectives and promoting a culture of respect and collaboration, we drive innovation and power global markets. Recruitment Fraud Alert If you receive an email from a spglobalind.com domain or any other regionally based domains, it is a scam and should be reported to reportfraud@spglobal.com. S&P Global never requires any candidate to pay money for job applications, interviews, offer letters, pre-employment training or for equipment/delivery of equipment. Stay informed and protect yourself from recruitment fraud by reviewing our guidelines, fraudulent domains, and how to report suspicious activity here. ----------------------------------------------------------- Equal Opportunity Employer S&P Global is an equal opportunity employer and all qualified candidates will receive consideration for employment without regard to race/ethnicity, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, marital status, military veteran status, unemployment status, or any other status protected by law. Only electronic job submissions will be considered for employment. If you need an accommodation during the application process due to a disability, please send an email to EEO.Compliance@spglobal.com and your request will be forwarded to the appropriate person. US Candidates Only The EEO is the Law Poster http://www.dol.gov/ofccp/regs/compliance/posters/pdf/eeopost.pdf describes discrimination protections under federal law. Pay Transparency Nondiscrimination Provision - https://www.dol.gov/sites/dolgov/files/ofccp/pdf/pay-transp_%20English_formattedESQA508c.pdf ----------------------------------------------------------- IFTECH103.2 - Middle Management Tier II (EEO Job Group)

Role: Junior AI/ML Engineer Location: Ambattur, Chennai(Onsite) Fulltime Position Job Summary: We are looking for an AI/ML Engineer to develop, optimize, and deploy machine learning models for real-world applications. You will work on end-to-end ML pipelines , collaborate with cross-functional teams, and apply AI techniques such as NLP, Computer Vision, and Time-Series Forecasting . This role offers opportunities to work on cutting-edge AI solutions while growing your expertise in model deployment and optimization. Key Responsibilities: Design, build, and optimize machine learning models for various business applications. Develop and maintain ML pipelines , including data preprocessing, feature engineering, and model training. Work with TensorFlow, PyTorch, Scikit-learn, and Keras for model development. Deploy ML models in cloud environments (AWS, Azure, GCP) and work with Docker/Kubernetes for containerization. Perform model evaluation, hyperparameter tuning, and performance optimization . Collaborate with data scientists, engineers, and product teams to deliver AI-driven solutions. Stay up to date with the latest advancements in AI/ML and implement best practices. Write clean, scalable, and well-documented code in Python or R. Technical Skills: Programming Languages: Proficiency in languages like Python. Python is particularly popular for developing ML models and AI algorithms due to its simplicity and extensive libraries like NumPy, Pandas, and Scikit-learn. Machine Learning Algorithms: Should have a deep understanding of supervised learning (linear regression, decision trees, SVM), unsupervised learning, and reinforcement learning. Data Management and Analysis: Skills in data cleaning, feature engineering, and data transformation are crucial. Deep Learning: Familiarity with neural networks, CNNs, RNNs, and other architectures is important. Machine Learning Frameworks and Libraries: Experience with TensorFlow, PyTorch, Keras, or Scikit-learn is valuable. Natural Language Processing (NLP): Familiarity with NLP techniques like word2vec, sentiment analysis, and summarization can be beneficial. Cloud Computing: Experience with cloud-based services like AWS SageMaker, Google Cloud AI Platform, or Microsoft Azure Machine Learning. Data Preprocessing: Skills in handling missing data, data normalization, feature scaling, and data transformation. Feature Engineering: Ability to create new features from existing data to improve model performance. Data Visualization: Familiarity with visualization tools like Matplotlib, Seaborn, Plotly, or Tableau. Containerization: Knowledge of containerization tools like Docker and Kubernetes. Databases : Understanding of relational databases (e.g., MySQL) and NoSQL databases (e.g., MongoDB). Data Warehousing: Familiarity with data warehousing concepts and tools like Amazon Redshift or Google BigQuery. Computer Vision: Understanding of computer vision concepts and techniques like object detection, segmentation, and image classification.

Your Role and Responsibilities 3+ years of experience in a Data Science, machine learning or a related field. Strong hands-on experience in Machine Learning and Statistics focusing on structured and unstructured data problems. Practical experience in several of the following areas: time series forecasting, clustering and classification techniques, regression, boosting algorithms, optimization techniques, NLP, recommendation systems, ElasticNet Excellent programming skills preferably in Python/Py spark and SQL Understanding of developing, implementing, deploying machine learning models on the cloud platforms(Azure, AWS, GCP) by using AWS/Azure Machine Learning, Data bricks, or other relevant cloud services Integrate machine learning models into existing systems and applications, ensuring seamless functionality and data flow Understanding of developing and maintaining MLOps pipelines for automated model training, testing, deployment, and monitoring Understanding of monitoring and analysing model performance, providing reports and insights to stakeholders as needed Familiarity with data processing and storage tools, such as SQL, Hadoop, or Spark Advanced engineering abilities to deliver flexible and scalable end-to-end machine learning solutions. Exposure to data visualization software and packages (Power BI, Tableau, matplotlib, d3) Understands challenges in business area, applicability of relevant data science disciplines, and system interactions. Excellent written and verbal communication skills, confidence in presenting ideas and findings to stakeholders, and ability to do so at the right level of detail. Required Technical and Professional Expertise Engineering Graduate from a reputed institute and/or Masters in Statistics, MBA 3+ years of Data science experience Strong expertise and deep understanding of machine learning. Strong understanding of SQL & Python. Knowledge of Power BI or Tableau is a plus Exposure to Industry specific (CPG, Manufacturing) use cases is required Strong client-facing skills Must be organized and detail oriented. Excellent communication and interpersonal skills Preferred Technical and Professional Experience Strong foundation in Supervised and Unsupervised Learning (Regression, Classification, Clustering, etc.). Proficiency in Ensemble Learning (Random Forest, Gradient Boosting, XGBoost, LightGBM, etc.). Experience in fine-tuning Large Language Models (LLMs) and working with open-source models (Llama, GPT, BERT, etc.). Familiarity with Prompt Engineering, RAG (Retrieval-Augmented Generation), and Fine-tuning techniques. Hands-on experience with Cloud Platforms (AWS, GCP, Azure) for ML model deployment. Familiarity with MLOps and Model Deployment using Kubernetes, Docker, and MLflow.

Machine Learning Engineer About Caliper: Caliper is an AI-enabled, comprehensive value-based care (VBC) risk analytics suite designed to provide affordable, accessible and actionable insights. Our solution empowers Community Care Providers to thrive in the VBC landscape, ensuring improved patient outcomes, operational efficiency and financial success. Position: Machine Learning Engineer (with NLP & AWS Experience) We are hiring a Machine Learning Engineer who brings strong foundational skills across ML workflows, with a working focus on Natural Language Processing (NLP) and experience deploying ML systems on AWS. This role is ideal for someone who is technically versatilecomfortable working across diverse machine learning problems including NLP, classification, forecasting, embeddings, and recommender systemswhile being hands-on with modern ML tooling, model lifecycle management, and cloud infrastructure. Key Responsibilities: Build and deploy ML models for a variety of use cases such as classification, prediction, NLP tasks, and recommender systems. Design, implement, and maintain end-to-end ML pipelines, including data preprocessing, model training, validation, and deployment. Apply NLP techniques where applicable (e.g., sentiment analysis, NER, document parsing, embeddings). Leverage AWS services (e.g., SageMaker, Lambda, S3, Bedrock, Comprehend) to deploy and scale ML solutions in production. Participate in model evaluation, monitoring, and retraining workflows. Collaborate with product, data, and engineering teams to understand requirements and translate them into ML-driven solutions. Support both experimental research and production-grade deployment workstreams. Required Skills & Experience: 4+ years of experience as a Machine Learning Engineer or Applied Scientist. Strong hands-on experience in core ML techniques: regression, classification, clustering, tree-based models, embeddings, etc. Solid Python programming skills and experience with libraries like Scikit-learn, PyTorch or TensorFlow, Pandas, NumPy. Exposure to NLP models and libraries (e.g., Hugging Face Transformers, spaCy, NLTK) with practical application experience. Experience deploying models using AWS cloud infrastructure, particularly SageMaker, Comprehend, Lambda, or Bedrock. Comfortable with model evaluation, metrics (e.g., accuracy, ROC-AUC, F1), and debugging pipelines in production. Experience working with version control, CI/CD tools, and basic MLOps practices. Nice to Have: Familiarity with Retrieval-Augmented Generation (RAG) pipelines and vector databases (e.g., FAISS, Milvus, Weaviate). Knowledge of prompt engineering or foundation model tuning (e.g., OpenAI, Claude, Bedrock). Experience with time series models, anomaly detection, or customer intelligence use cases. Exposure to Docker, Kubernetes, or Airflow for workflow orchestration. What We are Looking For: A generalist ML engineer who can adapt to evolving problem statements across NLP, tabular, or other ML use cases. Someone who balances code quality and experimentation, and can own model delivery end-to-end. A collaborative team player who is curious, self-driven, and excited to build in a fast-paced environment. Compensation will be commensurate with experience. If you are interested, please send your application to jobs@precognitas.com and For more information about our work, visit www.caliper.care

IMMEDIATE JOINERS ONLY Job Title: Senior MLOps Engineer Location : NCR Location (WFO) Note: DevOps -Knowledge is fine Experience Range: 6-12 years Primary Key skills: MLOps Key Responsibilities: Design, develop and maintain end-to-end MLOps pipelines for model deployment, monitoring, maintenance, and scalability. Automate the retraining, testing, and validation processes for ML models. Collaborate with cross-functional teams, including data science, software engineering and DevOps, to integrate ML models into production systems. Monitor model performance, diagnose issues, and implement improvements. Ensure scalability, reliability, and compliance of ML systems in production. Optimize infrastructure costs while maintaining high system performance. Stay up-to-date with the latest developments in MLOps, machine learning and AI, and apply new techniques to improve existing models and processes. Qualifications: Education: Bachelors or Master’s degree in Computer Science, Data Science, Statistics, Applied Mathematics, or a related field. Experience: Solid experience as a MLOps Engineer, Machine Learning Engineer, DevOps Engineer, or similar role. Experience in the retail industry or e-commerce is highly desirable. Technical Skills: Strong experience with Infrastructure as Code frameworks and languages (Terraform, Bicep or ARM) Strong programming skills in Python and experience with ML frameworks (TensorFlow, PyTorch, etc.). Hands-on experience with containerization (Docker) and orchestration tools (Kubernetes). Proficiency in CI/CD tools and cloud platforms (AWS, Azure, or Google Cloud). Knowledge of model monitoring and evaluation metrics. Familiarity with version control systems, such as Git, and model versioning tools like MLflow or DVC. Experience with Generative AI product deployment is desirable. Experience with big data using Databricks, Snowflake, Apache Spark or Hadoop is desirable. – some of these System level architecture understanding including scaling, MLOps, model/data monitoring, andensuring a deterministic pipeline. Soft Skills: Strong problem-solving skills with the ability to work independently and collaboratively in a fast-paced environment. Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders. A proactive attitude and a passion for continuous learning and innovation.

Precognitas Health Pvt. Ltd., a fully owned subsidiary of Foresight Health Solutions LLC, is seeking a Data Engineer to build and optimize our data pipelines, processing frameworks, and analytics infrastructure that power critical healthcare insights. Are you a bright, energetic, and skilled data engineer who wants to make a meaningful impact in a dynamic environment? Do you enjoy designing and implementing scalable data architectures, ML pipelines, automating ETL workflows, and working with cloud-native solutions to process large datasets efficiently? Are you passionate about transforming raw data into actionable insights that drive better healthcare outcomes? If so, join us! Youll play a crucial role in shaping our data strategy, optimizing data ingestion, and ensuring seamless data flow across our systems while leveraging the latest cloud and big data technologies. Required Skills & Experience : 4+ years of experience in data engineering, data pipelines, and ETL/ELT workflows. Strong Python programming skills with expertise in Python Programming, NumPy, Pandas, and data manipulation techniques. Hands-on experience with orchestration tools like Prefect, Apache Airflow, or AWS Step Functions for managing complex workflows. Proficiency in AWS services, including AWS Glue, AWS Batch, S3, Lambda, RDS, Athena, and Redshift. Experience with Docker containerization and Kubernetes for scalable and efficient data processing. Strong understanding of data processing layers, batch and streaming data architectures, and analytics frameworks. Expertise in SQL and NoSQL databases, query optimization, and data modeling for structured and unstructured data. Familiarity with big data technologies like Apache Spark, Hadoop, or similar frameworks. Experience implementing data validation, quality checks, and observability for robust data pipelines. Strong knowledge of Infrastructure as Code (IaC) using Terraform or AWS CDK for managing cloud-based data infrastructure. Ability to work with distributed systems, event-driven architectures (Kafka, Kinesis), and scalable data storage solutions. Experience with CI/CD for data workflows, including version control (Git), automated testing, and deployment pipelines. Knowledge of data security, encryption, and access control best practices in cloud environments. Strong problem-solving skills and ability to collaborate with cross-functional teams, including data scientists and software engineers. Compensation will be commensurate with experience. If you are interested, please send your application to jobs@precognitas.com. For more information about our work, visit www.caliper.care

Role: AI/ML Lead Engineer Location: Ambattur, Chennai(Onsite) Fulltime Position Job Summary: We are looking for an AI/ML Engineer to Lead, develop, optimize, and deploy machine learning models for real-world applications. You will work on end-to-end ML pipelines , collaborate with cross-functional teams, and apply AI techniques such as NLP, Computer Vision, and Time-Series Forecasting . This role offers opportunities to work on cutting-edge AI solutions while growing your expertise in model deployment and optimization. Key Responsibilities: Design, build, and optimize machine learning models for various business applications. Develop and maintain ML pipelines , including data preprocessing, feature engineering, and model training. Work with TensorFlow, PyTorch, Scikit-learn, and Keras for model development. Deploy ML models in cloud environments (AWS, Azure, GCP) and work with Docker/Kubernetes for containerization. Perform model evaluation, hyperparameter tuning, and performance optimization . Collaborate with data scientists, engineers, and product teams to deliver AI-driven solutions. Stay up to date with the latest advancements in AI/ML and implement best practices. Write clean, scalable, and well-documented code in Python or R. Technical Skills: Programming Languages: Proficiency in languages like Python. Python is particularly popular for developing ML models and AI algorithms due to its simplicity and extensive libraries like NumPy, Pandas, and Scikit-learn. Machine Learning Algorithms: Should have a deep understanding of supervised learning (linear regression, decision trees, SVM), unsupervised learning, and reinforcement learning. Data Management and Analysis: Skills in data cleaning, feature engineering, and data transformation are crucial. Deep Learning: Familiarity with neural networks, CNNs, RNNs, and other architectures is important. Machine Learning Frameworks and Libraries: Experience with TensorFlow, PyTorch, Keras, or Scikit-learn is valuable. Natural Language Processing (NLP): Familiarity with NLP techniques like word2vec, sentiment analysis, and summarization can be beneficial. Cloud Computing: Experience with cloud-based services like AWS SageMaker, Google Cloud AI Platform, or Microsoft Azure Machine Learning. Data Preprocessing: Skills in handling missing data, data normalization, feature scaling, and data transformation. Feature Engineering: Ability to create new features from existing data to improve model performance. Data Visualization: Familiarity with visualization tools like Matplotlib, Seaborn, Plotly, or Tableau. Containerization: Knowledge of containerization tools like Docker and Kubernetes. Databases : Understanding of relational databases (e.g., MySQL) and NoSQL databases (e.g., MongoDB). Data Warehousing: Familiarity with data warehousing concepts and tools like Amazon Redshift or Google BigQuery. Computer Vision: Understanding of computer vision concepts and techniques like object detection, segmentation, and image classification.