188 Machine Learning jobs in Coimbatore

Openings : Senior and Mid-Level

Location : Remote in India

Hours : IST

Rate: 25-35 LPA

Job Purpose

Analyzing, designing, developing and managing the data pipelines to release scalable Data Science models. The ML/Ops Engineer is expected to deploy, monitor and operate production grade AI systems in a scalable, automated and repeatable way.

Job Responsibilities

• Create and maintain a scalable code to deliver AI/ML processes.
• Design and implement the pipelines for building and deployment of ML models.
• Design dashboards to monitor a system.
• Collect metrics and create alerts based on them.
• Design and execute performance tests.
• Perform feasibility studies/analysis with a critical point of view.
• Support and maintain (troubleshoot issues with data and applications).
• Develop technical documentation for applications, including diagrams and manuals.
• Working on many different software challenges always and ensuring a combination of simplicity and
• maintainability within the code.
• Contribute to architectural designs of large complexity and size, potentially involving several distinct
• software components.
• Work as a member of a team, encouraging team building, motivation and cultivating effective team
• relations.

Required Experience

• Demonstrated experience and knowledge in Linux and Docker containers
• Demonstrated experience and knowledge in some of the main cloud providers (Azure, GCP or AWS)
• Proficient in programming languages: Python
• Experience with ML/Ops technologies like Azure ML
• Experience with SQL
• Experience in the use of collaborative developing tools such as Git, Confluence, Jira, etc.
• Strong ability to analyze and synthesize. (Good analytical and logical thinking capability)
• Proactive attitude, resolutive, used to work in a team and manage deadlines.
• Ability to learn quickly
• Agile methodologies development (SCRUM/KANBAN).
• Minimal work experience of 6 years with evidence.
• Ability to keep fluid communication written and oral in English, both written and spoken

Preferred Experience

• Demonstrated experience and knowledge in unit and integration testing
• Experience or Exposure with AI/ML frameworks: PyTorch, Onnx, Tensorflow
• Experience designing and implementing CICD pipelines for automation.
• Experience designing monitoring dashboards (Grafana or similar)

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.

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.

Key Responsibilities:

• Design and implement modular, reusable AI agents capable of autonomous decision-making using LLMs, APIs, and tools like LangChain, AutoGen, or Semantic Kernel.
• Engineer prompt strategies for task-specific agent workflows (e.g., document classification, summarization, labeling, sentiment detection).
• Integrate ML models (NLP, CV, RL) into agent behavior pipelines to support inference, learning, and feedback loops.
• Contribute to multi-agent orchestration logic including task delegation, tool selection, message passing, and memory/state management.
• Collaborate with MLOps, data engineering, and product teams to deploy agents at scale in production environments.
• Develop and maintain agent evaluations, unit tests, and automated quality checks for reliability and interpretability.
• Monitor and refine agent performance using logging, observability tools, and feedback signals.

Required Qualifications:

• Bachelor’s or Master’s in Computer Science, AI/ML, Data Science, or related field.
• 3+ years of experience in developing AI/ML systems; 1+ year in agent-based architectures or LLM-enabled automation.
• Proficiency in Python and ML libraries (PyTorch, TensorFlow, scikit-learn).
• Experience with LLM frameworks (LangChain, AutoGen, OpenAI, Anthropic, Hugging Face Transformers).
• Strong grasp of NLP, prompt engineering, reinforcement learning, and decision systems.
• Knowledge of cloud environments (AWS, Azure, GCP) and CI/CD for AI systems.

Preferred Skills:

• Familiarity with multi-agent frameworks and agent orchestration design patterns.
• Experience in building autonomous AI applications for data governance, annotation, or knowledge extraction.
• Background in human-in-the-loop systems, active learning, or interactive AI workflows.
• Understanding of vector databases (e.g., FAISS, Pinecone) and semantic search.

This is a remote position.

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.
  

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).

• 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: