Urgent: Senior Principal Consultant – ML Engineers

4 weeks ago


Gurugram Gurugram, India Genpact Full time

Job Description

Inviting applications for the role of Senior Principal Consultant - ML Engineers

In this role, lead the automation and orchestration of our machine learning infrastructure and CI/CD pipelines on public cloud (preferably AWS). This role is essential for enabling scalable, secure, and reproducible deployments of both classical AI/ML models and Generative AI solutions in production environments.

Responsibilities

- Develop and maintain CI/CD pipelines for AI/GenAI models on AWS using GitHub Actions and CodePipeline. (Not Limited to)

- Automate infrastructure provisioning using IAC. (Terraform, Bicep Etc)

- Any cloud platform - Azure or AWS

- Package and deploy AI/GenAI models on (SageMaker, Lambda, API Gateway).

- Write Python scripts for automation, deployment, and monitoring.

- Engaging in the design, development and maintenance of data pipelines for various AI use cases

- Active contribution to key deliverables as part of an agile development team

- Set up model monitoring, logging, and alerting (e.g., drift, latency, failures).

- Ensure model governance, versioning, and traceability across environments.

- Collaborating with others to source, analyse, test and deploy data processes

- Experience in GenAI project

Qualifications we seek in you

Minimum Qualifications

- experience with MLOps practices.

- Degree/qualification in Computer Science or a related field, or equivalent work experience

- Experience developing, testing, and deploying data pipelines

- Strong Python programming skills.

- Hands-on experience in deploying 2 - 3 AI/GenAI models in AWS.

- Familiarity with LLM APIs (e.g., OpenAI, Bedrock) and vector databases.

- Clear and effective communication skills to interact with team members, stakeholders and end users

Preferred Qualifications/ Skills

- Experience with Docker-based deployments.

- Exposure to model monitoring tools (Evidently, CloudWatch).

- Familiarity with RAG stacks or fine-tuning LLMs.

- Understanding of GitOps practices.

- Knowledge of governance and compliance policies, standards, and procedures

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