Python and ml frameworks (scikit-learn, tensorflow, pytorch)
The Machine Learning Engineer is responsible for designing, developing, deploying, and supporting AI/ML solutions from experimentation to production
Job Summary
The Machine Learning Engineer is responsible for designing, developing, deploying, and supporting AI/ML solutions from experimentation to production.
This role plays a key part in operationalizing machine learning and GenAI use cases through robust MLOps practices, reusable engineering patterns, and secure cloud-native implementations.
The engineer will collaborate closely with architects, product teams, and platform teams to deliver scalable, reliable, and responsible AI solutions that align with enterprise architecture and business goals.
Matching Summary
The Machine Learning Engineer is responsible for designing, developing, deploying, and supporting AI/ML solutions from experimentation to production.
Skills & Requirements
Must-have
Machine learning algorithms and model development
MLOps practices for model lifecycle
Python and ML frameworks (Scikit-learn, TensorFlow, PyTorch)
Cloud platforms (AWS, Databricks)
Software engineering, CI/CD, DevSecOps
Containerization and distributed data processing
Nice-to-have
GenAI patterns and agent frameworks
Responsible AI and model explainability
Intelligent automation platforms
Life Sciences or Healthcare domain knowledge
Critical-thinking and problem-solving skills
Communication and collaboration skills
Key Requirements
5 to 9 years of experience with software development