15h Left: Machine Learning Engineer
16 hours ago
This role is for one of the Weekday's clients Min Experience: 3 years Location: Bangalore JobType: full-time We are seeking a highly skilled Machine Learning Engineer to design, build, and scale production-ready ML systems. The ideal candidate will have a strong software engineering background, hands-on experience with ML frameworks, and a deep understanding of MLOps principles. You will be responsible for architecting model training, inference, and deployment pipelines that enable efficient experimentation and reliable performance at scale. Requirements What You’ll Do - Design and implement automated training and inference pipelines, including building a model registry system for artifact tracking, versioning, and lineage. - Develop frameworks for on-demand model training and architect parallel processing systems to support inference in event-driven environments. - Design and develop robust APIs that expose machine learning capabilities for internal and external use. - Build ETL pipelines and preprocessing frameworks tailored for ML applications. - Implement comprehensive monitoring solutions to identify performance bottlenecks and optimize system scalability. - Create infrastructure to support offline and online experimentation. - Build internal tools and frameworks that standardize ML workflows across teams and improve efficiency. - Stay up to date with emerging trends in machine learning engineering and MLOps, and evaluate new tools and best practices. - Contribute to technical architecture and decision-making to enhance ML infrastructure and platform capabilities. Required Qualifications - Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience. - 3+ years of experience in software engineering with a focus on machine learning systems. - Strong programming skills in Python and proficiency with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn. - Hands-on experience building and maintaining production-grade ML pipelines. - Proficiency with containerization tools like Docker and Kubernetes. - Experience working with cloud platforms (AWS, GCP, or Azure) and their ML services. - Strong understanding of software engineering best practices, including version control, CI/CD, and testing. - Experience with data processing frameworks for large-scale data workflows. - Excellent problem-solving skills and the ability to work independently on complex technical challenges. - Strong communication and collaboration skills to work effectively with cross-functional teams. Key Skills Machine Learning | Python | TensorFlow | PyTorch | Scikit-learn | MLOps | Docker | Kubernetes | Cloud Platforms (AWS/GCP/Azure) | CI/CD | ETL Pipelines
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▷ (15h Left) Machine Learning Engineer
4 weeks ago
Bengaluru, India Recro Full timeWhat would you be doing/ Expected from this role? • Collaborate with cross-functional teams including data scientists, engineers, and product managers to deliver AI-driven solutions. • Drive the architecture of machine learning pipelines from data collection and pre-processing to model training, evaluation, and deployment. • Implement scalable machine...
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15h Left! Machine Learning Engineer
5 days ago
Bengaluru, India Tata Consultancy Services Full timeRole - Machine Learning Required Technical Skill Set - Machine Learning, Data Scientist, R, Python, Azure DevOps Experience Range - 10 TO 15 Technical/Behavioral Competency - relevant experience in Machine Learning and modelling. - Hands on experience working on any of the data querying language SQL. - Hands on experience on any of the advanced analytics...
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(15h Left) Machine Learning Engineer
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Bengaluru, India Nexie Full timeJob 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...
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(15h Left) Senior Machine Learning Engineer
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Machine Learning Engineer
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Bengaluru, India Spydra Full timeJob Summary: We are seeking a talented and motivated Machine Learning Engineer to join our team. The ideal candidate will have a strong background in machine learning algorithms, data analysis, and software development. You will be responsible for designing, developing, and deploying machine learning models and systems that drive our products and...
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Machine Learning Engineer
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Bengaluru, India Spydra Full timeJob Summary: We are seeking a talented and motivated Machine Learning Engineer to join our team. The ideal candidate will have a strong background in machine learning algorithms, data analysis, and software development. You will be responsible for designing, developing, and deploying machine learning models and systems that drive our products and...
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(15h Left) Machine Learning Engineer
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Bengaluru, India eBay Full timeJob Description 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,...
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Machine Learning Engineer
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Bengaluru, Karnataka, India NatWest Group Full time ₹ 20,00,000 - ₹ 25,00,000 per yearMachine Learning Engineer,AVP Join us as a Machine Learning EngineerWe're looking for someone to deploy, automate, maintain and monitor machine learning models and algorithms to make sure they work effectively in a production environment Day-to-day, you'll collaborate with colleagues to design and develop state-of-the-art machine learning products which...
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Machine Learning Engineer
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Bengaluru, Karnataka, India TCP Corps Full time ₹ 12,00,000 - ₹ 24,00,000 per yearResponsibilities: • Develop, deploy, and maintain machine learning models using AWS Sagemaker and MLFlow. • Implement end-to-end ML pipelines, from data ingestion to model deployment. • Optimize model performance and scalability. • Collaborate with data scientists to transition models from development to production. • Implement Data Science...