42 Machine Learning jobs in Coimbatore

Position- Machine Learning Engineer

Experience - 3 to 5 years

Job Location - Pune / Remote

Immediate Joiner Only

Role Overview

The ML Ops Engineer plays a critical role in the development, automation, and deployment of Machine Learning (ML) and Generative AI (GenAI) pipelines across AWS cloud environments. This hands-on role emphasizes building reproducible workflows, integrating observability tools, and enabling efficient, scalable model delivery. The position supports AI systems deployed in banking environments, where resilience and reliability are paramount.

Key Experience:

• 3-5 years Strong programming skills in Python, with experience in pandas, SQL, and ML frameworks (e.g., scikit-learn).
• Should have used Python in ML domain to build, train and maintain models.
• Familiarity with AWS services such as Lambda, Glue, CloudWatch, and Bedrock.
• Experience with container workflows (Docker) and model lifecycle management.
• Foundational knowledge of observability practices and model deployment fundamentals.
• Interest or experience in supporting AI systems used by developers or analysts.
• Strong communication and documentation skills with a collaborative team mindset.
• Ability to assume ownership of assignments and consistently meet deadlines.

Responsibilities :

• Deploy and maintain ML and GenAI models using AWS services, including SageMaker, Fargate, and Bedrock.
• Apply prompt engineering techniques to optimize GenAI model performance and reliability.
• Experience with Retrieval-Augmented Generation (RAG) applications is a plus.
• Assist in building and maintaining internal model-serving platforms to support development teams.
• Implement containerized services using Docker and deploy them to AWS infrastructure.
• Write Infrastructure-as-Code (IaC) using Terraform to automate cloud resource provisioning (nice to have ).
• Participate in unit and end-to-end testing of ML pipelines, services, and monitoring workflows.
• Support model monitoring and health tracking using AWS CloudWatch and internal observability tools.
• Document internal systems and operational processes to ensure maintainability and reproducibility.

Looking for a culture to thrive & build a rewarding career for yourself, join the core team of young hustlers building the next generation of Machine Learning platform & services. You will develop training and deployment pipelines for machine learning, implement model compression algorithms, and productionize machine learning research solving challenging business problems.

Key Responsibilities:

• Design and develop generative AI models using techniques like RAG, transformers, and other relevant approaches.
• Fine-tune pre-trained LLMs for specific tasks and domains.
• Conduct research on new techniques for improving the performance and capabilities of generative AI models.
• Apply software engineering rigor and best practices to machine learning /Generative AI pipelines.
• Evaluate and analyse the performance of ML/generative AI models.
• Stay up to date on the latest advancements in generative AI research.
• Facilitate the development and deployment of proof-of-concept Generative AI systems.

Qualifications:

• Bachelor’s/Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
• 3-5 years of experience in generative AI or related fields.
• Experience in building data pipelines, deploying ML/GenAI models in production, and monitoring and maintaining their performance.
• Strong programming skills in Python.
• Familiarity with RAG and other techniques for building generative models.
• Extensive experience with Git, Docker and a good understanding of Linux for managing servers.
• Experience with cloud-based ecosystems, especially AWS ML/GenAI services.
• Exposure to ML/GenAI frameworks and tools.
• Excellent communication and collaboration skills.
• Ability to work independently and in a team-oriented environment.
• Methodical and meticulous towards work and planning

We are looking for an experienced Machine Learning Engineer to join our team. The ideal

candidate should have a strong background in developing, implementing, and deploying

machine learning models on edge platforms. With at least 5 years of overall experience and at

least 3 years of machine learning experience, you will significantly contribute to our projects,

driving innovation and delivering high-quality solutions.

Responsibilities:

● Design, develop, and deploy machine learning models and algorithms on the edge

platforms.

● Perform data analysis and feature engineering to enhance model performance.

● Collaborate with cross-functional teams to integrate ML solutions into existing systems.

● Monitor and maintain deployed models, ensuring optimal performance and reliability.

● Stay current with the latest advancements in machine learning and AI.

● Document processes and best practices for machine learning workflows.

● Troubleshoot and resolve issues related to ML models and data pipelines.

Experience & Background Requirement:

● Bachelor's or Master's degree in Engineering or equivalent.

● Minimum of 7+ years of overall experience.

● Minimum of 7 years of machine learning experience.

● Proficiency in programming languages such as Python, C, C++.

● Experience with any of HW platforms like NXP, NVidia, Qualcomm, Synaptcis .

● Strong understanding of machine learning algorithms and techniques (e.g., regression,

classification, clustering, neural networks).

● Experience with machine learning libraries and frameworks (e.g., TensorFlow, PyTorch,

Scikit-learn, Pandas, Numpy, Matplotlib, OpenCV).

● Knowledge of data preprocessing, feature engineering, and model training/evaluation.

● Experience with data storage and processing technologies (e.g., SQL, JSON, XML).

● Excellent problem-solving and analytical skills.

● Strong communication and collaboration abilities.

● Experience of streaming and GUI development is an advantage.

Branch Overview

Branch delivers world-class financial services to the mobile generation. With offices in the United States, Nigeria, Kenya, and India, Branch is a for-profit socially conscious company that uses the power of data science to reduce the cost of delivering financial services in emerging markets. We believe that everyone everywhere deserves fair financial access. The rapid spread of smartphones presents an opportunity for the world’s emerging middle class to access banking options and achieve financial flexibility.

Branch’s mission-driven team is led by the founder and former CEO of Kiva.org. The company presents a rich opportunity for our team members to drive meaningful growth in rapidly evolving and changing markets. In 2019, Branch announced our Series C and garnered more than $100M in funding with investments from leading Silicon Valley firms, including Andreessen Horowitz, Trinity Capital, Foundation Capital, Visa, and the International Finance Corporation (IFC).

As a company, we are passionate about our customers, fearless in the face of barriers, and driven by data. As a product-driven org, we value bottom-up innovation and decentralized decision-making. We believe the best ideas can come from anyone in the company, and we create an environment where everyone feels empowered to propose solutions to the challenges we face.

We value diversity and are committed to providing an inclusive working environment where human beings of all backgrounds can thrive.

Job Overview

Branch launched in India in early 2019 and has seen rapid adoption and growth. We are expanding our product portfolio as well as our user base in all our markets including India. We are looking for talented Machine Learning Engineers to join us and be part of this journey. You will work closely with other Engineers, Product Managers, and underwriters to develop, improve, and deploy machine learning models and to solve other optimization problems. We make extensive use of machine learning in our credit product, where it is used (among other things) for underwriting and loan servicing decisions. We are also actively exploring other applications of Machine Learning in some of our newer products, with the ultimate goal of improving the user experience.

Machine Learning sits at the intersection of a number of different disciplines: Computer Science, Statistics, Operations Research, Data Science, and others. At Branch, we fundamentally believe that in order for Machine Learning to be impactful, it needs to be closely embedded into the rest of the product development and software engineering process, which is why we emphasize the importance of software engineering skills and experience for this role.

As a company, we are passionate about our customers, fearless in the face of barriers, and driven by data. As an engineering team, we value bottom-up innovation and decentralized decision-making. We believe the best ideas can come from anyone in the company, and we are working hard to create an environment where everyone feels empowered to propose solutions to the challenges we face. We are looking for individuals who thrive in a fast-moving, innovative, and customer-focused setting.

Responsibilities

• Credit Decisions: Core to our business is understanding and building signals from unstructured and structured data to identify good borrowers.
• Customer Service: Using machine learning and LLM/NLP, automate customer service interactions and provide context to our customer service team.
• Fraud Prevention: Identify patterns of fraudulent behavior and build models to detect and prevent these behaviors.
• Team work: Bring your experience to bear on the technical direction and abilities of the team, and work cross-functionally with policy and product teams as we improve processes and break new ground.

Qualifications

• 2+ years of hands-on experience building software in a production environment. Startup or early-stage team experience is preferred.
• Excellent software engineering and programming skills, especially Python and SQL.
• A diverse range of data skills, including experimentation, statistics, and machine learning, and have used these skills to inform business decisions.
• A deep understanding of using cloud computing infrastructure and data pipelines in production.
• Self motivation: You teach yourself new skills. You take the initiative to solve problems before they arise. You roll up your sleeves and get stuff done.
• Team motivation: You listen to others, speak your mind, and ask the right questions. You are a great collaborator and teacher.
• The drive to make a positive impact on customers' lives.

Benefits of Joining

• Mission-driven, fast-paced, and entrepreneurial environment
• Competitive salary and equity package
• A collaborative and flat company culture
• Fully-paid Group Medical Insurance and Personal Accidental Insurance
• Unlimited paid time off, including personal leave, bereavement leave, and sick leave
• Fully paid parental leave — 6 months maternity leave and 3 months paternity leave
• Monthly WFH stipend alongside a one-time home office set-up budget
• $500 Annual professional development budget
• Team meals and social events — Virtual and In-person

We’re looking for more than just qualifications -- if you’re unsure that you meet the criteria but identify with our vision of providing equal opportunity to everyone to access financial services, please do not hesitate to apply!

Branch International is an Equal Opportunity Employer. The company does not and will not discriminate in employment on any basis prohibited by applicable law.

Hi,

We are hiring for our client, a Semi conductor industry in Coimbatore location.

Machine Learning Engineer:

Experience:1-1.5 years of Experience in Developing End-to-End Machine Learning solutions for Data-driven Decision making.

Skills Required:

Strong programming proficiency in Python and related libraries (NumPy, Pandas, Scikit-learn).

Experience with machine learning frameworks (TensorFlow, PyTorch, Keras).

Solid understanding of statistical modeling, data mining, and machine learning algorithms.

Conduct exploratory data analysis, feature engineering, and model selection.

Develop and implement machine learning models using appropriate algorithms and techniques (e.g., supervised, unsupervised, reinforcement learning).

Deploy and maintain machine learning models in production environments using cloud platforms or on-premises infrastructure.

Monitor model performance, identify areas for improvement, and retrain models as needed.

Knowledge of big data technologies (Hadoop, Spark)

Experience with time series analysis and forecasting.

Conduct A/B testing and experiment with different model architectures and hyperparameters.

Proficiency in data visualization tools (Matplotlib, Seaborn, Tableau, Power BI).

• Proven experience with JAX and NumPy in real-world ML projects
• Strong understanding of TensorFlow, including internals and model structure
• Experience with migrating models between frameworks and ensuring parity
• Solid grasp of ML training workflows, loop mechanics, and evaluation metrics
• Strong Python programming skills and clean, modular code practices
• Familiarity with ML experiment tracking and reproducibility tools (e.g., MLFlow, Weights & Biases)

Job Summary

We are looking for a highly skilled Technical Architect with expertise in AWS, Generative AI, AI/ML, and scalable production-level architectures. The ideal candidate should have experience handling multiple clients, leading technical teams, and designing end-to-end cloud-based AI solutions with an overall experience of 9-12 years.

This role involves architecting AI/ML/GenAI-driven applications, ensuring best practices in cloud deployment, security, and scalability while collaborating with cross-functional teams.

Key Responsibilities

Technical Leadership & Architecture

• Design and implement scalable, secure, and high-performance architectures on AWS for AI/ML applications.
• Architect multi-tenant, enterprise-grade AI/ML solutions using AWS services like SageMaker, Bedrock, Lambda, API Gateway, DynamoDB, ECS, S3, OpenSearch, and Step Functions.
• Lead full lifecycle development of AI/ML/GenAI solutions—from PoC to production—ensuring reliability and performance.
• Define and implement best practices for MLOps, DataOps, and DevOps on AWS.

AI/ML & Generative AI Expertise

• Design Conversational AI, RAG (Retrieval-Augmented Generation), and Generative AI architectures using models like Claude (Anthropic), Mistral, Llama, and Titan.
• Optimize LLM inference pipelines, embeddings, vector search, and hybrid retrieval strategies for AI-based applications.
• Drive ML model training, deployment, and monitoring using AWS SageMaker and AI/ML pipelines.

Cloud & Infrastructure Management

• Architect event-driven, serverless, and microservices architectures for AI/ML applications.
• Ensure high availability, disaster recovery, and cost optimization in cloud deployments.
• Implement IAM, VPC, security best practices, and compliance.

Team & Client Engagement

• Lead and mentor a team of ML engineers, Python Developer and Cloud Engineers.
• Collaborate with business stakeholders, product teams, and multiple clients to define requirements and deliver AI/ML/GenAI-driven solutions.
• Conduct technical workshops, training sessions, and knowledge-sharing initiatives.

Multi-Client & Business Strategy

• Manage multiple client engagements, delivering AI/ML/GenAI solutions tailored to their business needs.
• Define AI/ML/GenAI roadmaps, proof-of-concept strategies, and go-to-market AI solutions.
• Stay updated on cutting-edge AI advancements and drive innovation in AI/ML offerings.

Key Skills & Technologies

Cloud & DevOps

• AWS Services: Bedrock, SageMaker, Lambda, API Gateway, DynamoDB, S3, ECS, Fargate, OpenSearch, RDS
• MLOps: SageMaker Pipelines, CI/CD (CodePipeline, GitHub Actions, Terraform, CDK)
• Security: IAM, VPC, CloudTrail, GuardDuty, KMS, Cognito

AI/ML & GenAI

• LLMs & Generative AI: Bedrock (Claude, Mistral, Titan), OpenAI, Llama
• ML Frameworks: TensorFlow, PyTorch, LangChain, Hugging Face
• Vector DBs: OpenSearch, Pinecone, FAISS
• RAG Pipelines, Prompt Engineering, Fine-tuning

Software Architecture & Scalability

• Serverless & Microservices Architecture
• API Design & GraphQL
• Event-Driven Systems (SNS, SQS, EventBridge, Step Functions)
• Performance Optimization & Auto Scali