Senior Machine Learning Engineer

We are looking for a highly skilled Machine Learning Engineer (SDE-3) who can own end-to-end ML system development, including model building, production deployment, and MLOps pipeline management. The ideal candidate should have strong coding ability, excellent analytical thinking, and hands-on experience building scalable ML systems in production environments. This role offers an opportunity to work on cutting-edge AI solutions, including Deep Learning and LLM-based applications, powering intelligent automation systems.

End-to-End ML System Development The candidate will have responsibilities across the following functions

:

• Own the complete ML lifecycle: Problem formulation, Model development, Evaluation and optimisation, Production deployment and monitoring.
• Design and build scalable ML systems for real-world applications.

MLOps And Production Engineering

• Develop and maintain MLOps pipelines, including: Data ingestion and preprocessing, Model training and retraining workflows, CI/CD pipelines for ML models, Monitoring model performance and drift.
• Ensure production-grade reliability through: Model versioning, Performance optimisation, Fault tolerance and observability.

Machine Learning And AI Applications

• Work on a variety of ML problems, including: Regression and classification, Deep learning models, LLM-based applications and integrations.
• Build scalable inference and deployment systems for AI-driven applications.

Cross-Functional Collaboration

• Collaborate with Product, Data Engineering, and Platform teams to deliver impactful ML solutions.
• Translate business problems into scalable machine learning solutions.

The Core Requirements For The Job Include The Following Programming and Software Engineering:

• Strong programming skills in Python and/or Java.
• Ability to write clean, maintainable, and production-quality code.

Machine Learning Expertise

• Strong understanding of: Regression models, Classification algorithms, Deep learning techniques, Large Language Models (LLMs) and practical applications
• Hands-on experience with ML frameworks such as TensorFlow and PyTorch.

MLOps And Deployment

• Experience with: Model deployment (batch and real-time), CI/CD pipelines for ML, Monitoring and logging systems, Data pipeline integration.
• Experience building and managing scalable ML infrastructure in production.

Analytical Thinking

• Strong problem-solving and analytical skills.
• Ability to reason about trade-offs, scalability, and model performance.

Good To Have

• Strong ownership mindset, taking solutions from idea to production.
• Ability to work independently and drive technical decisions.
• Curious to stay updated with the latest trends in ML and AI.
• Ability to balance theoretical concepts with practical system constraints. This job was posted by Dhruv Parashar Talent Acquisition from GreyOrange.