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
You are sought for an integral role in a prestigious IT services, consulting, and business solutions organization with a 50-year history of global partnerships. As India's largest multinational business group, operating in 46+ countries, they boast over 500,000 highly trained consultants. Pioneering financial markets infrastructure and data business, they seek your expertise to enhance their dedication to excellence in Data & Analytics, Capital Markets, and post-trade services through open-access partnerships to shape the future of global service delivery.
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
