2871 Machine Learning Engineer jobs in Bengaluru

About Us:

At SFL, we are transforming India's youth sports academy ecosystem using technology, data, and strategic investments. Our goal is to empower academies with advanced AI tools, analytics, and operational support.

Position Overview:

We are looking for an ML Engineer to lead the development of our performance and learning tools. This is an individual contributor role where you will design, build, and fine-tune ML models for player analytics, skill assessment, and automated highlight generation.

We want someone who is passionate about sports and excited to create solutions that bring together computer vision, machine learning, and sports science. You will work closely with our product and engineering teams to turn these ideas into real products and take them to production.

Role & Responsibilities:

• Computer Vision & ML Models:
  Use computer vision and machine learning techniques to extract meaningful insights from sports videos and match data.
• MLOps:
  Build and maintain the end-to-end sports analytics ML platform – from video ingestion to production on AWS using best MLOps practices.
• Collaboration:
  Work with the product and tech teams to align on features and integration plans while independently owning AI product delivery.
• Continuous Improvement:
  Monitor model performance, gather feedback, and refine algorithms to improve accuracy and user experience.
• Data Management:
  Process and analyze structured and unstructured data including videos, scores, and stats to improve model accuracy.
• Ownership:
  High ownership in a fast-paced startup.

Basic Qualifications:

• Bachelor's degree in Computer Science or a related field.
• Strong problem-solving skills and a growth mindset.
• Hands-on experience in Python with OpenCV, PyTorch/TensorFlow and other ML libraries.
• 2–4 years of experience in training and deploying computer vision models in production.
• Practical experience working with AWS.
• Effective use of AI tools (Copilot, Cursor, Claude, ChatGPT etc.) to accelerate development and research workflows.

Preferred Qualifications:

• Strong academic background with a degree from IITs, NITs, IIITs, BITS Pilani, or other top-tier institutions.
• Knowledge of CNNs, transformers, object detection, and video analysis models.
• Expertise in Docker, MLFlow, AWS services such as MediaConvert and Sagemaker
• Experience in a large-scale consumer tech company.

Perks and Benefits:

• Competitive salary and performance-linked incentives.
• High ownership in building a greenfield AI product from scratch.
• Opportunity to impact youth sports in India through meaningful innovation.
• Flexible work environment with a learning-focused culture.

We help the world run better

At SAP, we keep it simple: you bring your best to us, and we'll bring out the best in you. We're builders touching over 20 industries and 80% of global commerce, and we need your unique talents to help shape what's next. The work is challenging – but it matters. You'll find a place where you can be yourself, prioritize your wellbeing, and truly belong. What's in it for you? Constant learning, skill growth, great benefits, and a team that wants you to grow and succeed.

We are seeking a motivated and curious Machine Learning Engineer to help build intelligent systems that power large-scale AI and large language model (LLM) capabilities. In this role, you will contribute to the design and development of modern infrastructure, collaborate with experienced engineers, and gain hands-on experience bringing ideas from concept to production—driving meaningful impact across SAP's global ecosystem.

Description

As part of our fast-moving team, you'll have the opportunity to work on AI and LLM-based systems at scale. We are looking for someone with strong programming skills, an eagerness to learn distributed systems, and the determination to tackle challenging technical problems. You'll work across a diverse technology stack, collaborate with teammates and product partners, and grow your expertise while contributing to high-impact AI initiatives.

Key Responsibilities:

• Develop and maintain backend services, APIs, and data pipelines in Go, Java, or Python
• Support the optimization of databases, services, and LLM infrastructure
• Work with modern technologies such as Kafka, Postgres, Hana, gRPC, and AI/ML frameworks
• Collaborate with senior engineers to learn best practices in system design and scalability.
• Partner with cross-functional teams to deliver features aligned with business goals

Minimum Qualifications:

• Bachelor's degree in Computer Science, Mathematics, Physics, or related field (or equivalent experience)
• 4 to 6 years of software engineering experience, ideally with exposure to backend or AI/ML systems
• Strong programming skills in at least one language (e.g., Python, Java, or Go)
• Familiarity with databases, APIs, or distributed systems concepts
• Basic understanding of CI/CD pipelines and modern development practices
• Good communication skills and ability to collaborate in diverse teams

Preferred Qualifications

• Personal or open-source projects that showcase your technical curiosity with AI/ML or LLM frameworks
• Interest in distributed systems and large-scale product development
• A problem-solving mindset and eagerness to learn new technologies

Why Join Us

• Work on cutting-edge AI and LLM systems used across SAP's global platforms
• Learn directly from experienced engineers in a supportive, collaborative environment
• Gain exposure to a wide range of modern tools and technologies
• Contribute to projects that help shape SAP's AI strategy and product capabilities

Bring out your best

SAP innovations help more than four hundred thousand customers worldwide work together more efficiently and use business insight more effectively. Originally known for leadership in enterprise resource planning (ERP) software, SAP has evolved to become a market leader in end-to-end business application software and related services for database, analytics, intelligent technologies, and experience management. As a cloud company with two hundred million users and more than one hundred thousand employees worldwide, we are purpose-driven and future-focused, with a highly collaborative team ethic and commitment to personal development. Whether connecting global industries, people, or platforms, we help ensure every challenge gets the solution it deserves. At SAP, you can bring out your best.

We win with inclusion

SAP's culture of inclusion, focus on health and well-being, and flexible working models help ensure that everyone – regardless of background – feels included and can run at their best. At SAP, we believe we are made stronger by the unique capabilities and qualities that each person brings to our company, and we invest in our employees to inspire confidence and help everyone realize their full potential. We ultimately believe in unleashing all talent and creating a better world.

SAP is committed to the values of Equal Employment Opportunity and provides accessibility accommodations to applicants with physical and/or mental disabilities. If you are interested in applying for employment with SAP and are in need of accommodation or special assistance to navigate our website or to complete your application, please send an e-mail with your request to Recruiting Operations Team:

For SAP employees: Only permanent roles are eligible for the SAP Employee Referral Program, according to the eligibility rules set in the SAP Referral Policy. Specific conditions may apply for roles in Vocational Training.

Qualified applicants will receive consideration for employment without regard to their age, race, religion, national origin, ethnicity, gender (including pregnancy, childbirth, et al), sexual orientation, gender identity or expression, protected veteran status, or disability, in compliance with applicable federal, state, and local legal requirements.

Successful candidates might be required to undergo a background verification with an external vendor.

AI Usage in the Recruitment Process

For information on the responsible use of AI in our recruitment process, please refer to our Guidelines for Ethical Usage of AI in the Recruiting Process.

Please note that any violation of these guidelines may result in disqualification from the hiring process.

Requisition ID: | Work Area: Software-Design and Development | Expected Travel: 0 - 10% | Career Status: Professional | Employment Type: Regular Full Time | Additional Locations: #LI-Hybrid

Machine Learning Engineer – Model Training & Optimization

About Unlox

Unlox is an AI-driven learning and career platform, trusted by universities and recognized by NASSCOM. We're building scalable AI systems to power personalized learning and career readiness for the next generation.

We are hiring a Machine Learning Engineer (Training & Optimization) who will focus on curating datasets, training, fine-tuning, and optimizing models to deliver high-performing AI systems.

Responsibilities

Curate and preprocess domain-specific datasets.

Train and fine-tune transformer-based models with LoRA, QLoRA, quantization, distillation.

Run experiments and track results to improve efficiency and accuracy.

Build training pipelines and evaluation systems for continuous improvement.

Collaborate with AI researchers and backend teams to integrate outputs into applications.

Requirements

Wrok Experience: 1 - 4 years

Proficiency in Python, PyTorch, and ML frameworks (Hugging Face, DeepSpeed, Accelerate).

Experience in fine-tuning transformer models.

Familiarity with tokenizer training, dataset pipelines, and evaluation benchmarks.

Knowledge of parameter-efficient tuning techniques.

Bonus

RLHF exposure or contributions to open-source AI projects.

Salary- As per market standards with performance based bonuses

Experience:- 6+ years of professional experience in Machine Learning Engineering, Software Engineering with a strong ML focus, or a similar role.

Exceptional Programming Skills: Expert-level proficiency in Python, including experience with writing production-grade, clean, efficient, and well-documented code. Experience with other languages (e.g., Java, Go, C++) is a plus.

Strong Software Engineering Fundamentals: Deep understanding of software design patterns, data structures, algorithms, object-oriented programming, and distributed systems.

At eBay, we're more than a global ecommerce leader — we're changing the way the world shops and sells. Our platform empowers millions of buyers and sellers in more than 190 markets around the world. We're committed to pushing boundaries and leaving our mark as we reinvent the future of ecommerce for enthusiasts.

Our customers are our compass, authenticity thrives, bold ideas are welcome, and everyone can bring their unique selves to work — every day. We're in this together, sustaining the future of our customers, our company, and our planet.

Join a team of passionate thinkers, innovators, and dreamers — and help us connect people and build communities to create economic opportunity for all.

Machine Learning Engineer

Date: Jul 3, 2025

Job Description

Looking for a company that inspires passion, courage and creativity, where you can be on the team shaping the future of global commerce? Want to shape how millions of people buy, sell, connect, and share around the world? If you're interested in joining a purpose driven community that is dedicated to crafting an ambitious and inclusive work environment, join eBay – a company you can be proud to be with.

Our Recommendations team works on delivering recommendations at scale and in near real time to our buyers on our website and native app platforms. Recommendations are a core part of how our buyers navigate eBay's vast and varied inventory. Our team develops state-of-the-art recommendations systems, including deep learning based retrieval systems for personalized recommendations, machine learned ranking models, GenAI/LLM powered recommendations, as well as advanced MLOps in a high volume traffic industrial e-commerce setting.

We are building cutting edge recommender systems powered by the latest ML, NLP, LLM/GenAI/RAG and AI technologies. Additionally, we are building production integrations with Google GCP Vertex AI platforms to supercharge our item recommendation algorithms. Come join our innovative engineering and applied research team

This Is An Opportunity To

• Influence how people will interact with eBay's recommender systems in the future, and how recommender systems technology will evolve
• Work with unique and large data sets of unstructured multimodal data representing eBay's vast and varied inventory, including billions of items and millions of users
• Develop and deploy state-of-the-art AI models to production which have direct measurable impact on eBay buyers
• Deploy big data technology and large scale data pipelines
• Drive marketplace GMB as well as advertising revenue via organic and sponsored recommendations

Qualifications

• MS in Computer Science or related area with 1+ years of relevant work experience (or BS/BA with 3+ years) in Engineering / Machine Learning / AI
• Experience building large scale distributed applications and expertise in an OO/functional language (Scala, Java, etc.)
• Experience building with no sql databases and key value stores (MongoDB, Redis, etc)
• Generalist with a can do attitude and willingness to learn/pick up new skill sets as needed
• Experience with using cloud services is a plus (GCP is a double plus)
• Experience with big data pipelines (Hadoop, Spark, Flink) is a plus
• Experience in AI applied research and industrial recommendation systems is a plus
• Experience with Large Language Models (LLMs) and prompt engineering is a plus

About Company :

They balance innovation with an open, friendly culture and the backing of a long-established parent company, known for its ethical reputation. We guide customers from what's now to what's next by unlocking the value of their data and applications to solve their digital challenges, achieving outcomes that benefit both business and society.

About Client:

Our client is a global digital solutions and technology consulting company headquartered in Mumbai, India. The company generates annual revenue of over $4.29 billion (₹35,517 crore), reflecting a 4.4% year-over-year growth in USD terms. It has a workforce of around 86,000 professionals operating in more than 40 countries and serves a global client base of over 700 organizations.

Our client operates across several major industry sectors, including Banking, Financial Services & Insurance (BFSI), Technology, Media & Telecommunications (TMT), Healthcare & Life Sciences, and Manufacturing & Consumer. In the past year, the company achieved a net profit of $53.4 million (₹4,584.6 crore), marking a 1.4% increase from the previous year. It also recorded a strong order inflow of $5 6 billion, up 15.7% year-over-year, highlighting growing demand across its service lines.

Key focus areas include Digital Transformation, Enterprise AI, Data & Analytics, and Product Engineering—reflecting its strategic commitment to driving innovation and value for clients across industries.

Proficient in Python language. Familiar with Tensorflow/Keras frameworks

ü Experience in building ML Pipeline and setup big data processing pipelines

ü Able to evaluate model and benchmark various model version on different data and report generation

ü Experience in Vision Domain ML models would be an advantage but not must have

ü Comfortable in generating data as per model format, tfrecords, lmdb or similar format.

ü Comfortable in data analysis and visualization

ü Knack for debugging of python compilation, data reading issues.

ü Proficiency in usage of different development tools – git/gerrit, static/dynamic analysis tools, code coverage, test & performance analysis tools

JOB DESCRIPTION:

JOB TITLE: ML Engineer

Location: Bengaluru

Exp:3+Years.

Good to have:

Comfortable with building data analysis, annotation scripts and exploring tools for ease of data understanding and annotations.

Knack for data debugging and verify which classes/types of data are causing the ML model to fail. Should be comfortable in writing scripts to filter out/analyze such images and should be able to draw a conclusion after verifying the failure cases

Experience in data visualization and cleaning for AI/ML projects.

Synthetic Data Generation experience

Able to track and version data used in ML pipeline and report generation

Passionbits
— a synthetic video ad engine that allows fashion and lifestyle brands to choose creators, scripts, wardrobes, and more to get custom videos made for their socials and ads.

Community of 3000+ creators & studios, powering on-demand video content for enterprise marketers. Helping creators monetise their on/behind camera skills, instead of their audience - to help add passive earnings

Pre-seed funded. Early revenue traction. Founding roles.

Role Description
We are seeking a passionate and talented Deep Learning Engineer to join our dynamic team. This role offers a unique opportunity to work on cutting-edge AI models that drive our video ad creation and optimization platform.

Responsibilities

• Model Development: Assist in designing, developing, and improving deep learning models for video generation and dynamic visual content creation.
• Research & Innovation: Conduct research on the latest advancements in deep learning and apply relevant techniques to enhance our platform.
• Data Processing: Analyze and preprocess large datasets to train and validate models, ensuring high-quality outputs.
• Integration: Collaborate with the engineering team to integrate AI models seamlessly into our existing systems.
• Optimization: Optimize model performance and scalability to ensure efficient deployment and real-time processing.
• Collaboration: Participate in brainstorming sessions to develop new features and enhancements for the platform.
• Documentation: Document your work and present findings to the team, ensuring clear communication of technical concepts.

Technical Skills

• Strong understanding of deep learning concepts and frameworks (e.g., TensorFlow, PyTorch).
• Proficiency in programming languages such as Python.
• Familiarity with computer vision techniques and video processing.

Soft Skills

• Excellent problem-solving skills and attention to detail.
• Ability to work independently and as part of a collaborative team.
• Strong communication skills, both written and verbal.

Preferred Experience

• With generative models (e.g., GANs, VAEs).
• Knowledge of video editing and processing tools.
• Previous internship or project experience in deep learning or AI development.

Skills: tensorflow,concepts,models,processing,deep learning,gans,pytorch,python

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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.)