2561 Machine Learning Engineer jobs in Bengaluru

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About the Company:

UptimeAI is leading the way in predictive analytics and AI-driven solutions to optimize operational uptime and reduce downtime for industrial and enterprise clients. Our innovative platform harnesses cutting-edge data science to deliver actionable insights, ensuring maximum efficiency and reliability. UptimeAI uniquely combines Artificial Intelligence with Subject Matter Knowledge from 200+ years of cumulative experience to explain interrelations across upstream/downstream equipment, adapt to changes, identify problems, and give prescriptive diagnosis like a human expert would.

About the Role:

We're looking for a highly skilled and hands-on ML End-to-End Engineer. You'll need deep practical experience across the entire machine learning lifecycle, from data ingestion and model development to robust backend integration and scalable production deployment. We want someone who not only understands the theory but can demonstrate significant real-world application and problem-solving at every stage of ML product development.

Responsibilities:

• ML Model Development & Optimization:
• Algorithm Proficiency: Proven experience designing, training, and optimizing diverse ML models, including strong expertise in supervised learning, and significant practical experience with unsupervised learning (e.g., clustering, dimensionality reduction, anomaly detection) and reinforcement learning algorithms (e.g., Q-learning, policy gradients). You should be able to discuss specific challenges encountered during model development across these paradigms and how you resolved them.
• Frameworks: Hands-on expertise with PyTorch, TensorFlow, and scikit-learn.
• Libraries: Strong proficiency with NumPy, Pandas, SciPy, Seaborn, and Plotly for data manipulation, analysis, and visualization.
• Feature Engineering: Demonstrable experience in effective feature engineering, selection, and transformation techniques.
• Data Engineering & Management for ML:
• Data Pipelining: Proven experience building and managing robust data pipelines for ML, including data ingestion, cleaning, transformation, and validation.
• Database Proficiency: Strong command of SQL and NoSQL databases (e.g., PostgreSQL, MongoDB) for storing and retrieving data relevant to ML models.
• Real-time Data Streams: Expertise with Apache Kafka for building and managing real-time data ingestion and processing pipelines.
• Backend Development for ML Applications:
• API Development: Demonstrable experience designing, building, and maintaining RESTful APIs for serving ML model predictions.
• Programming Language & Frameworks: Strong proficiency in Python with practical experience using either Flask or FastAPI for backend service development.
• System Design: Ability to design scalable, fault-tolerant, and high-performance backend systems to support ML inference.
• MLOps & Production Deployment:
• Containerization: Expertise in containerization technologies (e.g., Docker) for packaging ML models and their dependencies.
• Orchestration: Experience with container orchestration tools (e.g., Kubernetes) for deploying and managing ML services at scale.
• CI/CD for ML: Proven ability to set up and manage CI/CD pipelines specifically for ML model training, testing, and deployment (e.g., Jenkins, GitLab CI, GitHub Actions).
• Monitoring & Logging: Experience in implementing robust monitoring, alerting, and logging solutions for production ML systems to ensure performance, reliability, and data drift detection
• Model Performance & Reliability:
• Performance Tuning: Proven ability to identify and resolve performance bottlenecks in ML models and backend services. This includes experience with fine-tuning models and applying techniques to extract maximum performance from them, such as quantization, pruning, or model compression.
• Model Versioning & Experiment Tracking: Experience with tools and practices for model versioning, experiment tracking (e.g., MLflow, DVC), and reproducibility.
• General Engineering & Problem Solving:
• Competitive Coding / Algorithmic Problem Solving: Demonstrated proficiency in competitive coding platforms (e.g., LeetCode, HackerRank, TopCoder, Codeforces) or a strong, demonstrable foundation in algorithms and data structures, showcasing exceptional problem-solving abilities.
• Security Best Practices for ML Systems: Understanding and implementation of security best practices for ML models, data, and APIs.

Qualifications:

• 5+ years of experience as ML Engineer in high-growth SaaS or product startups
• Strong problem-solving and engineering mindset, with a keen eye for scalability, reliability, and efficiency.
• Excellent communication skills for conveying complex technical information to both technical and non-technical stakeholders.
• Adaptable and enthusiastic about working in a fast-paced, product-driven environment.
• Proactive in learning new ML technologies, backend frameworks, and deployment methodologies
• Comfortable working in a fast-paced, ambiguous startup environment

Why to join UptimeAI:

• Impact Industry-Wide Change: Contribute to transformative solutions that significantly improve operational efficiency and reliability for global clients.
• Collaborative and Growth-Oriented Environment: Join a talented, passionate team that values innovation, continuous learning, and professional growth.
• Opportunities for Leadership and Innovation: Lead pioneering projects, influence product development, and shape the future of industrial AI solutions.

Pay range and compensation package:

(Pay range or salary or compensation)

Equal Opportunity Statement:

(Include a statement on commitment to diversity and inclusivity.)

Job Title: Machine Learning Engineer (Founding Engineer)

Location: Bangalore, INDIA

Experience Level: Mid to Senior (3–5 years)

About Nexie

We’re building an AI-first platform that transforms how ecommerce brands connect with customers. Our agentic AI goes beyond simple automation — it thinks, creates, and adapts in real time to drive growth. The mission: make marketing feel effortless and intelligent.

Why Join

• Founding seat → shape the product & culture from scratch
• Work directly with serial founders (past startup → exit)
• Real equity + Competitive salary
• Build fast, ship fast, impact global brands

Your Role

• Own ML infra end-to-end: data → model → production
• Work on LLMs, embeddings, feedback loops, decision engines
• Rapid prototyping, user-driven iteration
• Push boundaries of AI agents in marketing

You Bring

• 3–5 yrs ML engineering (Python, PyTorch/TensorFlow, LLM APIs)
• Built & shipped ML systems (not just notebooks)
• Comfort with ambiguity, love for zero→one building

Bonus

• Agent systems / reasoning frameworks
• Ecommerce or martech exposure
• Interest in design/UX

We Value

Builders > employees. You’re curious, scrappy, and want to see your code shape the company’s DNA.

DM us or apply if you’re ready to build AI from the ground up.

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.

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.

Greetings.

TCS is currently hiring for a skilled Machine Learning Engineer. This opportunity offers an excellent chance to work in a dynamic and innovative environment. Please find the job description (JD) outlined below.

Experience : 10 - 16 years

Location :Pan India

Required skills:

Deep learning Frameworks (PyTorch, TensorFlow), Gen AI, LLM Fine-tuning, Deep learning Frameworks (PyTorch, TensorFlow), Gen AI, LLM Fine-tuning,

Gen AI Architectures (Transformers), Model Optimization and Performance Tuning

Builds and fine-tunes cutting-edge deep learning and generative AI models, particularly LLMs, for domain-specific AI applications. Requires expertise in deep learning frameworks and generative techniques to fine-tune and optimize high-performing models.

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.

What you will enjoy doing

• You will develop, train, test and deploy machine learning models in various fields such as

computer vision, LLMs, tabular and time series data.

• Experimenting with novel deep learning based technologies such as self-supervised learning

and generative AI will also be part of your tasks

• You will support in setting up the MLOps infrastructure for existing and new AI products

• Additionally you will work directly with customer data and set up data pipelines to collect,

curate, transform and version data

You'll be working in the Artificial Intelligence team, AI global corporate division engaged with real business challenges and opportunities in multiple countries. Focus of this role is to support the AI team with extending existing and building new AI products for a vast amount of uses cases across

business and value chain. You'll collaborate across different business and corporate functions in international team composed of Project Managers, Data Scientists, Data and Software Engineers

in the AI team and others in the Global AI team.

As a Machine Learning Enginee, you will be working closely with our global AI team to create and

implement sustainable AI models, algorithms, and software solutions for our global industrial gases and engineering services operations. You will participate in the collection, analysis, interpretation, and output of large amounts of data using advanced AI techniques like deep learning, NLP, and computer vision.

What Makes You Great

• You have a Bachelor or Masters Degree in Data Science, Computational

Statistics/Mathematics, Computer Science or related field

• You know the basics of neural networks and have an initial practical experience with deep

learning frameworks like PyTorch and Tensorflow.

• You have experience in backend and API development with Python (FastAPI, Flask) or similar

• You demonstrate knowledge of and basic practical experience with Object Oriented

Programming, design patterns, algorithms and data structures, version control systems (e.g.

Git)

• Having basic experience with cloud platforms (e.g. Azure), Docker and Kubernetes is a plus

• Fluent English

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.