2471 Machine Learning jobs in Tamil Nadu

Job Description:

We are seeking a Machine Learning Engineer with 3 years of experience and a creative mindset and technical expertise to join our R&D team. This role bridges the gap between cutting-edge AI advancements and creative video solutions. The ideal candidate is passionate about crafting and evaluating video content while leveraging machine learning and deep learning to revolutionize the field.

Responsibilities:

Machine Learning Expertise:

• Train, fine-tune, and deploy machine learning models efficiently.
• Develop pipelines and workflows to integrate AI into video production processes.
• Apply foundational knowledge of ML and DL to solve complex challenges.

Creative Video Development:

• Ability to conceptualize and create high-quality, consumable video content.
• Evaluate and critique video editing quality, suggesting creative improvements.
• Propose and implement innovative ideas to enhance the storytelling experience.

Language and Diffusion Models:

• Should understand the fundamentals of LLM and diffusion models
• Utilize language models and diffusion models to generate, enhance, or manipulate creative outputs effectively.
• Stay updated with advancements in generative AI and optimize its use in video workflows.

Research and Innovation:

• Keep abreast of the latest research in AI, ML, and computer vision.
• Read and interpret research papers from top conferences such as SIGGRAPH, CVPR, ICCV, and NeurIPS to inform project decisions.

Collaboration and Teamwork:

• Work seamlessly with backend and frontend development teams to ensure smooth integration of AI-driven tools.
• Foster a collaborative environment, contributing to brainstorming and cross-functional initiatives.

Requirements:

• Creative Thinking: Proven ability to generate original video concepts and critique existing video content.
• Technical Skills: Strong foundation in machine learning and deep learning, with experience in model training and deployment.
• Research Aptitude: Familiarity with top-tier research publications and a demonstrated ability to implement state-of-the-art techniques.
• Generative AI Proficiency: Hands-on experience with language and diffusion models. ● Team Player: Excellent interpersonal skills with a history of successfully working in collaborative team environments.
• Adaptability: Ability to stay updated with rapid advancements in technology and incorporate them into workflows.
• Graduate from IIT, IIIT or NIT will be preferred

Company Description

Founded in 2018, Giggso is a responsible AI platform for enterprise operations with security and automations. Giggso provides a single integrated platform for AI Agent orchestration, AI governance, monitoring and observability, incident management, automation, and remediation.

The platform is web 3.0 and blockchain-enabled, offering Model Risk Management solutions. Giggso aims to enhance decision-making and drive efficiency in AI ML systems for better customer experiences and cost management.

Role Description

This is a full-time hybrid role for a Machine Learning Engineer at Giggso, located in Chennai with flexibility for remote work. The Machine Learning Engineer will be responsible for pattern recognition, developing neural networks, implementing statistical analysis, and optimizing algorithms for AI ML systems. The role involves working on complex AI ML systems and contributing to operational efficiency and risk management.

Qualifications

• Pattern Recognition, Neural Networks, and Algorithms skills
• LLM programming with strong NLP background
• Strong background in python and math reasoning
• Proficiency in Statistics
• Ability to develop and optimize algorithms for AI ML systems
• Experience with pattern recognition and neural network modeling
• Knowledge of statistical analysis techniques
• Demonstrated expertise in algorithm design and implementation
• Strong problem-solving and analytical skills
• Understanding of model deployment and monitoring processes
• Master's is needed while PhD in Computer Science, Statistics, or related field is a plus

Job Description -

We are seeking a Machine Learning Engineer to assist in developing and implementing object detection and AI-based predictions. You will have the opportunity to work on real-world applications and contribute to the development of novel algorithms. As a ML engineer, you’ll collaborate with our team and works various applied AI/ML tasks.

Key Responsibilities -

• Assist in training and fine-tuning ML models for real-time AI-based tasks.
• Work with large datasets to prepare, annotate, preprocess, and augment data for training purposes.
• Implement and test model architectures to improve accuracy, speed, and performance.
• Help analyze and optimize model performance based on results and metrics.
• Document research and findings, contributing to team knowledge and project reports.
• Participate in code reviews and contribute to software development best practices.
• Stay updated with the latest trends and research in computer vision and applied ML.

Qualifications -

• Bachelor's or master's degree program in Computer Science, Electrical Engineering, or a related field.
• Solid understanding of AI/ML concepts, data cleaning, synthetic data generation and other relevant concepts.
• Hands-on experience with MLOps.
• Hands-on experience with YOLO or similar deep learning object detection frameworks (e.g., Faster R-CNN, SSD).
• Proficiency in programming languages such as Python
• Experience with OpenCV and Pytorch is a must.
• Experience with Statistical Analysis and modeling is a plus.
• Experience with CUDA and GPU acceleration is a plus.
• Experience with ROS and C++ is also a huge plus.
• Strong problem-solving skills, attention to detail, and a collaborative mindset.

Preferred Skills -

• Knowledge of data cleaning techniques and data preprocessing methods.
• Familiarity with version control systems like Git .
• Experience in deploying models into production environments (optional).
• Exposure to ROS and OpenCV in C++.

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About the Company

Candidate will be responsible for designing and developing applications for automating business processes, language understanding systems using NLP for text representation techniques more efficiently.

About the Role

The candidate will be required to conceive, design, develop NLP applications, develop application for document automation using python, pytorch and should be familiar with advanced libraries used in python and other programming languages.

Responsibilities

• Develop and deploy applications like document automation, summarization, creation of user interface, query based chatbot.
• Understand business objectives and develop AI/ML models that help to achieve the same, along with metrics to track their progress.

Qualifications

• Bachelor’s/master’s degree in computer science or engineering with a focus on language processing.
• At least 7+ years of experience with exposure to NLP and relevant projects.

Required Skills

• Experience with AI/ML platforms, frameworks, and libraries.
• Knowledge in relevant programming languages, development tools, databases.
• Proficiency in programming in Python, Pytorch, tensorflow.
• Understanding of NLP techniques for text representation, semantic extraction techniques, data structures, and modeling.
• Capable of writing and building components to integrate into new or existing systems.
• Documentation experience for complex software components.
• Experience in implementing product lifecycle - design, development, quality, deployment, maintenance.
• Ready to work within a collaborative environment with teams.
• Creative thinking for identifying new opportunities.

Preferred Skills

• Experience in projects which required working with natural language data such as nltk (Python), Apache OpenNLP or GATE.
• Knowledge of advanced desktop and web interface development, chatbot support interfaces etc.

About the Role

MLOps Engineer is responsible to help deploy, scale, and manage machine learning models in production environments. You will work closely with data scientists and engineering teams to automate the machine learning lifecycle, optimize model performance, and ensure smooth integration with data pipelines.

Responsibilities

• Bachelor's degree in computer science, analytics, mathematics, statistics.
• Strong experience in Python, SQL, Pyspark.
• Solid understanding and knowledge of containerization technologies (Docker, Podman, Kubernetes).
• Proficient in CI/CD pipelines, model monitoring, and MLOps platforms (e.g., AWS SageMaker, Azure ML, MLFlow).
• Proficiency in cloud platforms, specifically AWS, Azure and GCP.
• Familiarity with ML frameworks such as TensorFlow, PyTorch, Scikit-learn.
• Familiarity with batch processing integration for large-scale data pipelines.
• Experience with serving models using FastAPI, Flask, or similar frameworks for real-time inference.
• Certifications in AWS, Azure or ML technologies are a plus.
• Experience with Databricks is highly valued.
• Strong problem-solving and analytical skills.
• Ability to work in a team-oriented, collaborative environment.

Qualifications

• Bachelor's degree in computer science, analytics, mathematics, statistics.

Required Skills

• Model Development & Tracking: TensorFlow, PyTorch, scikit-learn, MLflow, Weights & Biases
• Model Packaging & Serving: Docker, Kubernetes, FastAPI, Flask, ONNX, TorchScript
• CI/CD & Pipelines: GitHub Actions, GitLab CI, Jenkins, ZenML, Kubeflow Pipelines, Metaflow
• Infrastructure & Orchestration: Terraform, Ansible, Apache Airflow, Prefect
• Cloud & Deployment: AWS, GCP, Azure, Serverless (Lambda, Cloud Functions)
• Monitoring & Logging: Prometheus, Grafana, ELK Stack, WhyLabs, Evidently AI, Arize
• Testing & Validation: Pytest, unittest, Pydantic, Great Expectations
• Feature Store & Data Handling: Feast, Tecton, Hopsworks, Pandas, Spark, Dask
• Message Brokers & Data Streams: Kafka, Redis Streams
• Vector DB & LLM Integrations (optional): Pinecone, FAISS, Weaviate, LangChain, LlamaIndex, PromptLayer.

Preferred Skills

• Experience with Databricks is highly valued.
• Certifications in AWS, Azure or ML technologies are a plus.

Dear Candidate,

Greetings from HCL Tech!

We are hiring Data scientist – Machine Learning requirement

Below is the JD for your perusal:

JD:

• Develop and implement AI models capable of accurate predictions.

• Analyze input data to identify key factors influencing rapid movements, utilizing data-driven insights.

• Establish and maintain a continuous learning framework to update models based on planner feedback.

Skills:

• Expert in AI and machine learning model development

• Strong programming knowledge in Python

Rate your self on below Skils

AI models

Machine Learning

Python

If interested, kindly revert this mail with the details in the below format along with updated resume

Name

Contact Number

Email ID

Current Location

Preferred Location

Total Experience

Relevant Experience

Current Organisation

Current CTC

Expected CTC

Notice Period

Regards

Durga Karunakaran

HCL Technologies Ltd.

Job Title:

ML Ops Engineer / ML Engineer

Experience - 5Yrs -10 Yrs

Location - Chennai

Job Overview:

We are looking for an experienced MLOps Engineer to help deploy, scale, and manage machine learning models in production environments. You will work closely with data scientists and engineering teams to automate the machine learning lifecycle, optimize model performance, and ensure smooth integration with data pipelines.

Key Responsibilities:

Transform prototypes into production-grade models

• Assist in building and maintaining machine learning pipelines and infrastructure across cloud platforms such as AWS, Azure, and GCP.
• Develop REST APIs or FastAPI services for model serving, enabling real-time predictions and integration with other applications.
• Collaborate with data scientists to design and develop drift detection and accuracy measurements for live models deployed.
• Collaborate with data governance and technical teams to ensure compliance with engineering standards.

Maintain models in production

• Collaborate with data scientists and engineers to deploy, monitor, update, and manage models in production.
• Manage the full CI/CD cycle for live models, including testing and deployment.
• Develop logging, alerting, and mitigation strategies for handling model errors and optimize performance.
• Troubleshoot and resolve issues related to ML model deployment and performance.
• Support both batch and real-time integrations for model inference, ensuring models are accessible through APIs or scheduled batch jobs, depending on use case.

Contribute to AI platform and engineering practices

• Contribute to the development and maintenance of the AI infrastructure, ensuring the models are scalable, secure, and optimized for performance.
• Collaborate with the team to establish best practices for model deployment, version control, monitoring, and continuous integration/continuous deployment (CI/CD).
• Drive the adoption of modern AI/ML engineering practices and help enhance the team’s MLOps capabilities.
• Develop and maintain Flask or FastAPI-based microservices for serving models and managing model APIs.

Minimum Required Skills:

• Bachelor's degree in computer science, analytics, mathematics, statistics.
• Strong experience in Python, SQL, Pyspark.
• Solid understanding and knowledge of containerization technologies (Docker, Podman, Kubernetes).
• Proficient in CI/CD pipelines, model monitoring, and MLOps platforms (e.g., AWS SageMaker, Azure ML, MLFlow).
• Proficiency in cloud platforms, specifically AWS, Azure and GCP.
• Familiarity with ML frameworks such as TensorFlow, PyTorch, Scikit-learn.
• Familiarity with batch processing integration for large-scale data pipelines.
• Experience with serving models using FastAPI, Flask, or similar frameworks for real-time inference.
• Certifications in AWS, Azure or ML technologies are a plus.
• Experience with Databricks is highly valued.
• Strong problem-solving and analytical skills.
• Ability to work in a team-oriented, collaborative environment.

Tools and Technologies:

Model Development & Tracking: TensorFlow, PyTorch, scikit-learn, MLflow, Weights & Biases

Model Packaging & Serving: Docker, Kubernetes, FastAPI, Flask, ONNX, TorchScript

CI/CD & Pipelines: GitHub Actions, GitLab CI, Jenkins, ZenML, Kubeflow Pipelines, Metaflow

Infrastructure & Orchestration: Terraform, Ansible, Apache Airflow, Prefect

Cloud & Deployment: AWS, GCP, Azure, Serverless (Lambda, Cloud Functions)

Monitoring & Logging: Prometheus, Grafana, ELK Stack, WhyLabs, Evidently AI, Arize

Testing & Validation: Pytest, unittest, Pydantic, Great Expectations

Feature Store & Data Handling: Feast, Tecton, Hopsworks, Pandas, Spark, Dask

Message Brokers & Data Streams: Kafka, Redis Streams

Vector DB & LLM Integrations (optional): Pinecone, FAISS, Weaviate, LangChain, LlamaIndex, PromptLayer

AI/ML ENGINEER

Who We Are?

Cleantech Industry Resources accelerates United States solar, battery storage and EV projects by providing turnkey development as a service including 100% internal systems engineering. The company deploys a leading team that spun out of the largest solar power producer in the world. This team operates within a sophisticated suite of software to support projects from land origination, through to commercial operation.

Location

Chennai

What We Offer

• Opportunity to join a top-notch, collaborative team of professionals
• Fantastic team environment and collaborative culture
• Professional development opportunities to grow into an industry leader
• Medical Insurance for the employee and family
• Spot Recognition bonus for exceptional performance
• Long Term Incentive policy
• Regular team outings, events, and activities to foster a positive work environment

Our Commitment to Diversity

At CIR, we are dedicated to nurturing a diverse and equitable workforce that truly reflects our community. We deeply value each person’s unique perspective, skills, and experiences. CIR embraces all individuals, regardless of race, religion, sexual orientation, gender identity, age, or nationality. We are steadfast in our commitment to fostering a just and inclusive world through intentional policies and actions. Your individuality enriches our collective strength, and we strive to ensure everyone feels respected, valued, and empowered.

Position Summary

We are looking for an AI/ML Engineer to build and optimize machine learning models for GIS-based spatial analysis and data-driven decision-making. This role involves working on geospatial AI models, data pipelines, and Retrieval-Augmented Generation (RAG)-based applications for zoning, county sentiment analysis, and regulatory insights. The engineer will also work closely with the data team, leading efforts in data curation and building robust data pipelines to collect, preprocess, and analyse extensive datasets from various geospatial and regulatory sources to generate automated reports and insights.

Core Responsibilities

Machine Learning for GIS & Spatial Analysis:

• Develop and deploy ML models for geospatial data processing, forecasting, and automated GIS insights.
• Work with large-scale geospatial datasets (e.g., satellite imagery, shapefiles, raster/vector data).
• Create AI models for land classification, feature detection, and geospatial pattern analysis.
• Optimize spatial data pipelines and build predictive models for environmental and energy sector applications.

Retrieval-Augmented Generation (RAG) & NLP Development:

• Develop RAG-based AI applications to extract insights from zoning, permitting, and regulatory documents.
• Build LLM-based applications for zoning law interpretation, county sentiment analysis, and compliance predictions.
• Implement document retrieval and summarization techniques for legal, policy, and energy development reports.

Data Engineering & Pipeline Development:

• Lead the creation of ETL pipelines to collect and preprocess geospatial data for ML model training.
• Work with PostGIS, PostgreSQL, and cloud storage to manage structured and unstructured data.
• Collaborate with the data team to design and implement efficient data processing and storage solutions.

AI Model Optimization & Deployment:

• Fine-tune LLMs for domain-specific applications in renewable energy and urban planning.
• Deploy AI models using cloud-based MLOps frameworks (AWS, GCP, Azure).
• Optimize ML model inference for real-time GIS applications and geospatial data analysis.

Collaboration & Continuous Improvement:

• Work with cross-functional teams to ensure seamless AI integration with existing business processes.
• Engage in knowledge sharing and mentoring within the company.
• Stay updated with latest advancements in AI, GIS, and NLP to improve existing models and solutions.

Education Requirements

Master’s in Computer Science, Data Science, Machine Learning, Geostatistics, or related fields.

Technical Skills and Experience

Software Proficiency:

• Programming: Python (TensorFlow, PyTorch, scikit-learn, pandas, NumPy), SQL.
• Machine Learning & AI: Deep learning, NLP, retrieval-based AI, geospatial AI, predictive modeling.
• GIS & Spatial Data Processing: Experience with PostGIS, GDAL, GeoPandas, QGIS, Google Earth Engine.
• LLM & RAG Development: Experience in fine-tuning LLMs, retrieval models, vector databases (FAISS, Weaviate).
• Cloud & MLOps: AWS/GCP/Azure, Docker, Kubernetes, MLflow, FastAPI.
• Big Data Processing: Experience with large-scale data mining, data annotation, and knowledge graph techniques.
• Database & Storage: PostgreSQL, NoSQL, vector databases, cloud storage solutions.
• Communication: Strong ability to explain complex AI/ML concepts to non-technical stakeholders.

Project Management:

• Design experience in projects from conception to implementation.
• Ability to coordinate with other engineers and stakeholders.

Renewable Energy Systems:

• Understanding of solar energy systems and their integration into existing infrastructure

Experience

• 2-4 years of experience
• Experience in developing AI for energy sector, urban planning, or environmental analysis.
• Strong understanding of potential prediction, zoning laws, and regulatory compliance AI applications.
• Familiarity with spatiotemporal ML models and satellite-based geospatial analytics.

Psychosocial Skills /Human Skills/Behavioural Skills

• Strong analytical, organizational, and problem-solving skills.
• Management experience a plus.
• Must be a go-getter with an enterprising attitude
• A self-starter, able to demonstrate high levels of initiative and motivation
• Entrepreneurial mindset with the ability to take ideas and run with them from concept to conclusion.
• Technical understanding of clean energy business processes
• Exceptional verbal and writing communication skills with superiors, peers, partners, and other stakeholders.
• Excellent interpersonal skills while managing multiple priorities in a fast-paced and ever-changing environment.

Physical Demands

The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. The physical demands of this job require an individual to be able to work at a computer for most of the day, be able to participate in conference calls and travel to team retreats on a time-to-time basis. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

Work Conditions

The work environment is usually quiet (normal city traffic noises are common), a blend of artificial and natural light, temperate and generally supports a collaborative work environment. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

Equal Opportunity Employer

At Cleantech Industry Resources, we embrace diversity and uphold a strong dedication to establishing an all-encompassing atmosphere for both our staff and associates. Our choices in employment are free from any bias related to race, creed, nationality, ethnicity, gender, sexual orientation, gender identity, gender expression, age, physical limitations, veteran status, or any other legally safeguarded attributes.

Being an integral part of Cleantech Industry Resources means you can expect to be immersed in a realm of professional possibilities within a culture that nurtures teamwork, adaptability, and the embracing of all.

Job Title:

ML Ops Engineer / ML Engineer

Experience - 5Yrs -10 Yrs

Location - Chennai

Job Overview:

We are looking for an experienced MLOps Engineer to help deploy, scale, and manage machine learning models in production environments. You will work closely with data scientists and engineering teams to automate the machine learning lifecycle, optimize model performance, and ensure smooth integration with data pipelines.

Key Responsibilities:

Transform prototypes into production-grade models

• Assist in building and maintaining machine learning pipelines and infrastructure across cloud platforms such as AWS, Azure, and GCP.
• Develop REST APIs or FastAPI services for model serving, enabling real-time predictions and integration with other applications.
• Collaborate with data scientists to design and develop drift detection and accuracy measurements for live models deployed.
• Collaborate with data governance and technical teams to ensure compliance with engineering standards.

Maintain models in production

• Collaborate with data scientists and engineers to deploy, monitor, update, and manage models in production.
• Manage the full CI/CD cycle for live models, including testing and deployment.
• Develop logging, alerting, and mitigation strategies for handling model errors and optimize performance.
• Troubleshoot and resolve issues related to ML model deployment and performance.
• Support both batch and real-time integrations for model inference, ensuring models are accessible through APIs or scheduled batch jobs, depending on use case.

Contribute to AI platform and engineering practices

• Contribute to the development and maintenance of the AI infrastructure, ensuring the models are scalable, secure, and optimized for performance.
• Collaborate with the team to establish best practices for model deployment, version control, monitoring, and continuous integration/continuous deployment (CI/CD).
• Drive the adoption of modern AI/ML engineering practices and help enhance the team’s MLOps capabilities.
• Develop and maintain Flask or FastAPI-based microservices for serving models and managing model APIs.

Minimum Required Skills:

• Bachelor's degree in computer science, analytics, mathematics, statistics.
• Strong experience in Python, SQL, Pyspark.
• Solid understanding and knowledge of containerization technologies (Docker, Podman, Kubernetes).
• Proficient in CI/CD pipelines, model monitoring, and MLOps platforms (e.g., AWS SageMaker, Azure ML, MLFlow).
• Proficiency in cloud platforms, specifically AWS, Azure and GCP.
• Familiarity with ML frameworks such as TensorFlow, PyTorch, Scikit-learn.
• Familiarity with batch processing integration for large-scale data pipelines.
• Experience with serving models using FastAPI, Flask, or similar frameworks for real-time inference.
• Certifications in AWS, Azure or ML technologies are a plus.
• Experience with Databricks is highly valued.
• Strong problem-solving and analytical skills.
• Ability to work in a team-oriented, collaborative environment.

Tools and Technologies:

Model Development & Tracking: TensorFlow, PyTorch, scikit-learn, MLflow, Weights & Biases

Model Packaging & Serving: Docker, Kubernetes, FastAPI, Flask, ONNX, TorchScript

CI/CD & Pipelines: GitHub Actions, GitLab CI, Jenkins, ZenML, Kubeflow Pipelines, Metaflow

Infrastructure & Orchestration: Terraform, Ansible, Apache Airflow, Prefect

Cloud & Deployment: AWS, GCP, Azure, Serverless (Lambda, Cloud Functions)

Monitoring & Logging: Prometheus, Grafana, ELK Stack, WhyLabs, Evidently AI, Arize

Testing & Validation: Pytest, unittest, Pydantic, Great Expectations

Feature Store & Data Handling: Feast, Tecton, Hopsworks, Pandas, Spark, Dask

Message Brokers & Data Streams: Kafka, Redis Streams

Vector DB & LLM Integrations (optional): Pinecone, FAISS, Weaviate, LangChain, LlamaIndex, PromptLayer