ML Engineer

Your job

• You will actively own & manage client deliverables.
• Collaborate with data scientists, data engineers, and other MLOps Engineers to solve complex problems and create unique solutions for MLOps
• Create ML prototypes, design ML systems, research, and implement ML algorithms, and develop machine learning applications in accordance with client needs.
• Should have implementation experience of model evaluation and model + data validation tools/ techniques such as schema validation, valuation metrics etc.
• Responsible for developing and deploying CI/CD based automated ML application pipelines (collection, processing, cleaning, transformation etc.) along with the CT component for continuous feedback loop for re-training
• Strong skills in Feature store setup, Pipeline Integration, Automated triggering, Model Continuous Delivery, Model Serving (via APIs) & Model Monitoring
• Ensure output’s thorough quality check & provide analytics driven insights and next steps
• To perform statistical analysis and fine-tune models using test results.
• Understand data and different platforms used by the client.
• Actively contribute towards problem solving & mentor juniors in the team
• Can work hands-on independently

Capabilities

• You should have relevant experience in ML Engineering/ ML Ops role with an end-to-end understanding of ML-based project’s solution designing, development, implementation & deployment
• Should fulfill all the standard MLOps level 2 requirements for CI/CD + CT pipeline automation
• Strong grasp & hands-on experience with production-ready scalable code using SQL (advance) and Python, along with an in-depth knowledge of Machine Learning concepts
• Hands-on experience in working on the AWS cloud stack
• Working experience Sagemaker, EC2, S3, EMR, Lambda Functions, Cloudwatch, etc.
• At least 2 years of experience in orchestrating ML Jobs on Airflow, Step Functions, Model registry, etc.

Qualifications

Bachelor of Engineering, Bachelor Computer Science or Master's Degree