The position is suited for individuals who have the ability to work in a constantly challenging environment and deliver effectively and efficiently. As a MLOps Engineer, you will be an integral member of our Data & Analytics team responsible for design and development of pipelines using cutting edge technologies.

Key Responsibilities :

- As an ML practitioner, you will be supporting the Data Science group and actively participating in the entire lifecycle of a data science project, including exploratory data analysis, feature engineering, model creation, and model optimization to boost performance and accuracy.

- It is important that the person in this role is proactive and independent.

- Should be a problem solver with an open mind and an eagerness to pick up new skills.

- Develop, test, and deploy machine learning/AI models.

- Collaborate daily with Data Science Managers/Senior Data Scientists and work on the feedback received for the work to develop your skills and ensure alignment with workstream objectives.

- Be a contributor to the planning and direction of a project and effectively prioritize your tasks and objectives.

- Contribute to internal discussions on emerging machine learning methodologies.

- Perform Natural Language Processing

- Drive workload balancing and execution across labs/products.

- Perform the responsibilities of Tech Lead for projects.

- Responsible for deploying and operationalizing MLOps, particularly in terms of model training, automated retraining, version management, and governance.

- Tasked with receiving models from data scientists, establishing and applying benchmarks and metrics, and ensuring ML systems are available and accessible to the necessary systems.

- Must guarantee that the training data is accurately processed using comparable data pre-processing methods to prevent discrepancies in model evaluation and performance.

The Team :

Analytics + Information Management (AIM) is one of the major service lines within Technology practice of Deloitte US India Consulting org. Service lines are comprised of capability areas, and that focuses on helping clients manage and leverage their information. AIM capability areas Information Delivery, Data Management & Architecture, Performance Management Technologies, and Advanced Analytics Enablement.

Qualifications :

- 3 to 7 years work experience on AWS ML Ops SageMaker,

- Expert in in languages and tools - Python, R, Scala, MATLAB

- Familiarity with AI and machine learning model development life cycles

- Demonstrated ability to write complex code.

- Excellent problem-solving and analytical skills.

- Strong communication and collaboration skills to work with cross-functional teams.

- Follow and suggest new DS best practices.

- Partner with business on OKRs

- Thought leader in at least 1 broad AIML area.

Primary Skills :

- AWS ML Ops