Senior Machine Learning Engineer - Deep Learning

Senior Machine Learning Engineer Applied AI | Bangalore (FANG hiring)

Are you passionate about building scalable, intelligent systems that solve real-world problems?

Do you enjoy transforming cutting-edge machine learning research into production-ready solutions?

We are hiring a Senior Machine Learning Engineer for our Applied AI team based in Bangalore.

This is a high-impact role where youll work at the intersection of software engineering and data science to bring AI solutions to life.

What You'll Do :

- Lead the design, development, and deployment of machine learning models into scalable, production environments.

- Build robust, testable ML pipelines and APIs using strong software design principles.

- Collaborate with data scientists to develop and optimize models (supervised, deep learning, RL, etc.

- Implement MLOps best practices: CI/CD for ML, model versioning, monitoring, and automation.

- Design data pipelines for model training, inference, and performance tracking.

- Work with cross-functional teams to integrate ML into core products.

- Stay current with ML advancements and propose practical innovations.

What We're Looking For :

- 4-9+ years of hands-on experience in ML engineering or related roles.

- Strong Python programming skills; exposure to other languages like Java, C++, or Go is a plus.

- Solid understanding of software design patterns, algorithms, and distributed systems.

- Experience with ML frameworks like PyTorch or Scikit-learn.

- Skilled in feature engineering, model evaluation, and performance tuning.

- Familiar with SQL/NoSQL databases and big data handling.

- Strong communication skills and the ability to simplify technical topics.

Preferred Qualifications :

- Masters or PhD in Computer Science, Data Science, or a related field.

- Experience with tools like Spark, Kafka, or Hadoop.

- Exposure to A/B testing and experimentation frameworks.

- Contributions to open-source or a strong personal project portfolio.

- Understanding of ML model governance, bias mitigation, and privacy standards.