1686 Machine Learning jobs in Bengaluru

``html

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.

Job Title: ML Engineer - Partnership Track

Company: FastCode.AI

Location: Bangalore (In-office, 5 days/week)

About FastCode.AI: We're a 30-person AI/ML company building production systems for major clients. Half our team operates as partners - owning projects, managing P&L, and taking home percentages instead of just salaries. We believe in rapid growth through osmosis - 12 of our engineers started with zero ML experience and now lead complex projects.

About This Role: We're hiring exactly 2 ML Engineers who will join our partnership track. You don't need ML experience - our founder (PhD Max Planck, ex-Apple, ex-Weta Digital) and team will teach you. In 5-8 months, you'll be leading RAG pipelines, training models, and managing client relationships.

What You'll Do:

• Build and deploy ML systems for enterprise clients

• Own end-to-end projects from architecture to production

• Work directly with clients on requirements and delivery

• Progress from engineer to partner, managing your own P&L

• Collaborate with a team that ships code surviving Friday deploys

We're Looking For:

• Strong mathematical foundations and first-principles thinking

• High agency - you see problems and ship solutions without waiting for tickets

• Direct communication style - you push back with data

• Production mindset with emphasis on testing and monitoring

• Humility paired with ambition and hunger to grow

• Ability to write clearly and think systematically

Requirements:

• Bachelor's degree in any engineering discipline (or equivalent experience)

• Strong programming fundamentals

• Comfort with back-of-envelope calculations

• Willingness to work from our Bangalore office 5 days/week

Nice to Have: • Experience with Python (but we'll teach you) • Exposure to statistics/probability • Any technical project you're proud of

Compensation: ₹12-24 LPA based on experience + partnership track with revenue sharing

How to Apply: Application deadline: September 8, 2024, 8:00 AM IST

Email arjun+ with:

1. 150 words explaining why you're our next success story
2. Description of one hard problem you've solved (technical or otherwise)
3. Your LinkedIn profile link

We value clear thinking and strong writing. Show us both.

Why FastCode.AI: • Learn directly from industry veterans who've worked at Apple, Weta Digital, and published with Yann LeCun • Join alumni who've gone on to lead ML at US startups, co-found companies, and become professors • Transition from employee to partner - some 23-year-old partners out-earn senior engineers • Work on real production systems for major clients, not POCs • Grow faster than anywhere else - we've proven it works

Note: We're closing this role for 3 months after these 2 hires to focus on onboarding.

FastCode.AI is an equal opportunity employer committed to building a diverse and inclusive team.

Job Title: Cloud and MLOps Developer

Location: Bangalore

Required Skills:

• Hands-on experience with cloud platforms (AWS, Azure, or GCP).
• Proficiency in MLOps tools like MLflow, Kubeflow, or SageMaker Pipelines.
• Strong knowledge of Docker, Kubernetes , and container orchestration.
• Proficient in Python, Bash , and basic scripting for automation.
• Experience with CI/CD tools and version control systems (e.g., Git).
• Familiarity with data and model versioning tools like DVC.
• Good understanding of machine learning lifecycle and ML model management.
• Knowledge of networking, security, and infrastructure automation .

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.

Role - MLOps Engineer

Experience - 5+ Yrs

Location - Remote

Responsibilities:

● Build and optimize model serving infrastructure with a focus on inference latency and cost

optimization

● Architect efficient inference pipelines that balance latency, throughput, and cost across

various acceleration options

● Develop monitoring and observability solutions for ML systems

● Collaborate with ML Engineers to establish best practices for optimized model deployment

● Implement cost-efficient, enterprise-scale solutions

● Collaborate in a cross-functional, distributed team for continuous system improvement

● Work with MLEs, QA Engineers, and DevOps Engineers

● Evaluate and implement new technologies and tools

● Contribute to architectural decisions for distributed ML systems

Experience and Qualifications:

● 5+ years of experience in software engineering with Python

● Experience with ML frameworks, particularly PyTorch

● Experience optimizing ML models with hardware acceleration (AWS Neuron , ONNX,

TensorRT)

● Experience with AWS ML services and hardware-accelerated instances (Sagemaker,

Inferentia, Trainium)

● Proven experience building and operating AWS serverless architectures

● Deep understanding of event-driven processing patterns, SQS/SNS and serverless caching

solutions

● Experience with containerization using Docker and orchestration tools

● Strong knowledge of RESTful API design and implementation

● Proficiency in writing good quality & secure code and be familiar with static code analysis

tools

● Excellent analytical, conceptual and communication skills in spoken and written English

● Experience applying Computer Science fundamentals in algorithm design, problem solving,

and complexity analysis