28,854 Machine Learning Engineer jobs in India

At WTMF , we’re on a mission to build not just an AI app, but an AI bestie — someone you can journal with, share your moods, plan your days, or just talk to when you need it. To make that work, we need a Machine Learning Engineer who can turn ideas into working systems that scale.

This isn’t about research that lives in a PDF. It’s about taking models, making them efficient, and putting them in the hands of real people across the globe.

Someone who:

• Knows their way around ML pipelines like others know their way around Google Maps.
• Gets a thrill out of optimizing inference speed or reducing model size.
• Can wrangle messy datasets without losing patience (or hair).
• Thinks “deployment” is where the real fun begins.

• Build and optimize ML pipelines that power our journaling, mood tracking, and conversational features.
• Work with LLMs, embeddings, and classifiers to make WTMF smarter over time.
• Turn messy, real-world data into structured insights our AI can learn from.
• Collaborate with AI/ML researchers, backend engineers, and product designers to bring features from idea to production.
• Keep an eye on performance, scalability, and cost so our models run fast, smooth, and responsibly.

• Solid experience with ML frameworks (PyTorch, TensorFlow, or similar).
• Comfort with building and deploying ML systems end-to-end.
• Strong data engineering fundamentals (ETL, feature pipelines, distributed systems).
• Good grasp of statistics and optimization (you know why the model overfit before anyone asks).
• Bonus: hands-on work with cloud platforms (AWS/GCP/Azure) and MLOps tools.

• You’ll be making ML work in the wild — powering an AI companion that users actually talk to every day.
• You’ll see your models improve real conversations, not just benchmarks.
• Competitive pay, equity options, and the freedom to work remotely.
• A small, ambitious team where your contributions shape the product directly.

Glance - An InMobi Group Company

Founded in 2019, Glance is a consumer technology company that operates disruptive digital platforms including Glance, Roposo, and Nostra. Glance’s ’smart lock screen’ inspires consumers to make the most of every moment by surfacing relevant experiences without the need for searching and downloading apps. Glance Lock Screen is currently available on over 450 million smartphones worldwide. Roposo is a LIVE platform that is revolutionizing live experiences, through a unique, immersive, creator-led approach. Nostra is the largest gaming platform in India and Southeast Asia, offering gamers engaging ways to discover, play, watch, learn and compete.

Headquartered in Singapore, Glance is an unconsolidated subsidiary of InMobi Group and is funded by Jio Platforms, Google, and Mithril Capital. For more information visit glance.com, nostra.gg, and roposo.com

What should you know about joining Glance?

At Glance, we walk the talk – free yourself, dream big, and chase your passion! On joining, you’ll have opportunities to make an immediate impact on mission-critical projects, as you work with highly capable and ambitious peer groups.

Be rewarded for your autonomy even as you collaborate. Ideate, innovate, and inspire by leveraging bleeding-edge tech to disrupt consumer experiences.

While you work, we’ll take care of nourishing your body, mind, and soul. This includes daily meals, gym, trainings, tech tools, and regular unwind sessions. Also, feel free to bring your kids – even the furry ones – to the office!

What You Will Be Doing

As a Machine Learning Engineer , you will help design, develop, and deploy scalable ML systems and services that power consumer experiences across Glance platforms. You will work closely with Data Scientists and cross-functional teams to drive ML solutions from ideation to production.

Key Responsibilities:

• Architect and implement end-to-end ML pipelines for experimentation, model development, and deployment.
• Build microservices and APIs to serve ML models and AI-driven features.
• Design and develop proof-of-concepts and scalable AI/ML-based products.
• Collaborate with product, engineering, and content (newsroom) teams to define, test, and launch new ML features.
• Explore and integrate new tools, platforms, algorithms, and ML frameworks.
• Own project delivery with a focus on performance, reliability, and scalability.
• Document solutions and communicate effectively with stakeholders.

What We’re Looking For

• 5+ years of hands-on experience as an ML Engineer, with a track record of delivering real-world ML solutions.
• Strong background in Computer Science, Mathematics, or Statistics (Bachelor’s, Master’s, or PhD).
• Proven ownership of end-to-end ML projects, from prototype to production.
• Solid experience working with Recommender Systems and personalization.
• Proficiency in Python , Golang , Spark , and related open-source ML/data frameworks.
• Strong understanding of statistics, algorithms , and applied math.
• Ability to work independently and collaboratively in cross-functional teams.
• Excellent technical documentation and communication skills.
• Experience in a research-driven or data science-intensive environment is a plus.

Job description

Job Title: Machine Learning Engineer

Salary: Upto INR 25,000 per month, all-inclusive. Contract employment.

Location: (Remote)

Experience: Minimum 2 years in machine learning / data science.

About Us:

We have built

and we are Amalaan India Pvt Ltd , a 4-year-old, dynamic and forward-thinking company focused on leveraging cutting-edge technology to solve complex problems in data processing and machine learning.

We are building out SaaS solutions for our global B2B and B2C clients and customers. Each solution we provide is unique. We are a product development company (not a body shop). This means, you will always be faced with new challenges and exciting opportunities to grow your knowledge on how successful products are built in the real world.

About the Role:

We’re looking for a Machine Learning Engineer who can take models from idea to production. You’ll work on datasets across different domains, experiment with modern ML techniques, and help build intelligent features into our SaaS products.

This role is ideal for someone who loves both the theory and practice of ML — from building models to deploying them at scale.

What You’ll Do:

• Build, train, and validate ML models for real-world applications.
• Preprocess, clean, and analyze structured/unstructured datasets.
• Work with deep learning frameworks (PyTorch / TensorFlow) and traditional ML libraries (scikit-learn).
• Collaborate with product and engineering teams to integrate models into production.
• Optimize models for speed, scalability, and reliability.
• Document workflows, experiments, and results.
• Stay updated with the latest research and tools in ML/AI.

What We’re Looking For:

• Minimum 2 years of experience in machine learning / data science.
• Strong Python skills with hands-on experience in ML libraries.
• Experience with at least one deep learning framework (PyTorch / TensorFlow).
• Understanding of data preprocessing, feature engineering, and evaluation metrics.
• Familiarity with cloud ML services (AWS/GCP/Azure) is a plus.
• Knowledge of MLOps tools (Docker, MLflow, CI/CD) is an advantage.
• Strong problem-solving skills and ability to work independently.

What We Offer:

• The latest in AI and ML tools and technologies to work with.
• An inclusive and innovative work environment.
• Opportunities for professional growth and development.
• Competitive salary and benefits package.
• Flexible working hours, remote and work-from-home options.

How to Apply:

• Apply via LinkedIn
• Send your resume and cover letter to
• Include links to your GitHub/Kaggle projects or ML work (preferred)

Hiring: MLOps Engineer | Bangalore (Hybrid – 4 Days WFO)

Job Title: MLOps Engineer

Location: Bangalore (Hybrid – 4 days work from office)

Job Type: Full-Time

Experience: 3+ years

About the Role

We are looking for a passionate MLOps Engineer who can bridge the gap between Data Science and Production systems. You’ll work with Data Scientists, DevOps, and Software Engineers to build scalable ML infrastructure, automate workflows, and ensure smooth deployments.

Key Responsibilities

• Design, develop & maintain CI/CD pipelines for ML models
• Collaborate with Data Scientists to deploy scalable ML solutions
• Automate validation, retraining & monitoring pipelines
• Ensure reliability, security & scalability of ML infrastructure
• Manage containerized ML apps using Docker & Kubernetes
• Monitor model performance & data drift in production

Required Skills

• 3+ years in MLOps / DevOps / ML Engineering
• Strong in Python, Bash & scripting
• Experience with ML platforms (MLflow / Kubeflow / SageMaker)
• Cloud expertise (AWS / Azure / GCP )
• CI/CD tools (Jenkins, GitHub Actions, etc.)
• Mandatory: Experience in Psypark

Preferred Skills

• IaC tools (Terraform)
• Data engineering / ETL pipelines
• Monitoring tools (Prometheus, Grafana)

Why Join?

• Work at the intersection of AI, DevOps & Scalability
• Contribute to production-grade ML systems
• Growth-focused role with cutting-edge tech exposure

Exp:3+ years

Budget: 18 lpa

Key Responsibilities:

• Design and implement ML models for personalization, recommendations, NLP, and agentic AI systems.
• Build, test, and deploy ML models to production.
• Create and optimize feature engineering pipelines.
• Collaborate with cross-functional teams to integrate ML solutions.
• Monitor and improve model performance.

Required Skills:

• Strong Python skills (NumPy, Pandas, Scikit-learn).
• Deep learning with PyTorch or TensorFlow.
• Experience with recommendation libraries (LightFM, Surprise).
• Knowledge of LangChain/AutoGPT for agentic AI.
• NLP expertise with Hugging Face Transformers.
• Experience deploying ML models to production.

Qualifications:

• Advanced degree in Computer Science, ML, or related field.
• 3+ years of relevant ML/AI experience.

Machine Learning Engineer

About Astreya:

Astreya offers comprehensive IT support and managed services. These services include Data

Center and Network Management, Digital Workplace Services (like Service Desk, Audio Visual, and

IT Asset Management), as well as Next-Gen Digital Engineering services encompassing Software

Engineering, Data Engineering, and cybersecurity solutions. Astreya's expertise lies in creating

seamless interactions between people and technology to help organizations achieve operational

excellence and growth.

Responsibilities:

• Design, develop, and deploy machine learning models and algorithms to solve complex business problems and drive data-driven decision making
• Collaborate with cross-functional teams including data engineers, software engineers, and business stakeholders to understand requirements and translate business objectives into scalable ML solutions
• Build and maintain robust ML pipelines for data preprocessing, feature engineering, model training, validation, and deployment
• Optimize model performance through hyperparameter tuning, feature selection, and algorithmic improvements
• Implement MLOps best practices including model versioning, monitoring, and automated retraining workflows
• Ensure data quality, integrity, and security throughout the ML lifecycle
• Scale ML systems to handle large datasets and high-throughput inference requirements
• Conduct A/B testing and experimentation to validate model performance and business impact
• Monitor deployed models for drift, performance degradation, and bias detection
• Create comprehensive documentation including technical specifications, model cards, and deployment guides for stakeholders

Professional & Technical Skills:

• Must have strong proficiency in Python and experience with core ML libraries such as scikit-learn, XGBoost, LightGBM, and CatBoost
• Must have hands-on experience with deep learning frameworks including TensorFlow, PyTorch
• Must have solid understanding of machine learning algorithms, statistical methods, and model evaluation techniques
• Must have experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies Docker or Kubernetes
• Need to have proficiency in SQL and experience working with both structured and unstructured datasets
• Need to have knowledge of big data technologies such as Spark, Hadoop, or distributed computing frameworks
• Must be familiar with MLOps tools and platforms such as MLflow, Kubeflow, or similar model lifecycle management systems
• Must have experience with version control systems (Git) and CI/CD pipelines for ML workflows
• Need to have knowledge of data visualization tools and libraries such as Matplotlib, Seaborn, Plotly, or Tableau
• Must be familiar with software engineering best practices, including code testing, debugging, and performance optimization
• Need to have understanding of software development methodologies such as Agile or Scrum
• Possess excellent analytical and problem-solving skills with ability to work independently and in team environments

Additional Information:

• Must have Bachelor's or Master's degree in Computer Science, Machine Learning, Statistics, Mathematics, or related quantitative field
• Preferred 3+ years of experience in machine learning engineering or related roles
• Preferred experience with real-time inference systems and model serving architectures

Preferred knowledge of specialized domains such as computer vision, natural language processing, or recommendation systems