AWS SageMaker - ML and GEN AI Engineer

ECMS Req #

ECMS#527449,527448,527447 - AWS SageMaker – ML and GEN AI Engineer

Role

Senior Lead Data Scientist

Number of Openings

3

Duration of project

6-12 months(initial contract 3 months, later extended based on project)

No of years' experience

5+ years

Detailed job description - Skill Set:

The AWS SageMaker Engineer (Gen AI, LLMs, & NLP) will design, develop, and deploy advanced machine learning models, focusing on Generative AI, Large Language Models (LLMs), Agentic AI, traditional AI, and Natural Language Processing (NLP) using AWS SageMaker and AWS Bedrock. This role involves leveraging Python and deep learning frameworks to build scalable, intelligent systems for tasks like text generation, sentiment analysis, autonomous decision-making, and more, using models such as LLaMA or similar. The engineer will collaborate with data scientists, AI researchers, and DevOps teams to deliver production-ready AI solutions that align with business objectives.

Key Responsibilities:

• Model Development: Build, train, and fine-tune Gen AI, LLMs, Agentic AI, and traditional AI models using AWS SageMaker and AWS Bedrock, including deep learning models for NLP tasks (e.g., text classification, entity recognition, summarization) and models like LLaMA.
• Fine-Tuning & Customization: Fine-tune pre-trained LLMs
• Experience:
• 4+years of experience in machine learning engineering, with expertise in Gen AI, LLMs, traditional AI, deep learning, and NLP.
• 6+ Hands-on experience with AWS Devops and AWS Bedrock for training, fine-tuning, and deploying AI models.
• Experience with open-source LLMs (e.g., LLaMA) or Bedrock-hosted models (e.g., Titan, Claude
• Experience with AWS Dev Ops, CI/CD integration. Kubernetes, Dockers
• Experience in Creating ML Flows using AWS Sagemaker
• Experience in using ML Models monitoring using clodwatch
• Experience in working with GEN AI, Langchain, Open AI Models and deployment of GEN AI models using AWS Sagemaker
• Experience in Deploying ML models using AWS sagemaker
• ML workflow orchestration and enabling CI/CD integration
• Experience with AWS services (e.g., S3, Lambda, Step Functions, Comprehend) and cloud architecture.

Soft Skills:

• Strong problem-solving and analytical skills.
• Excellent communication to convey complex AI/NLP concepts to non-technical stakeholders.
• Ability to thrive in collaborative, fast-paced environments.

Mandatory Skills

AWS Sagemaker Professional with ML, NLP, GEN AI and Dev Ops experience.

Vendor Billing range

8000-9000 per day depending on experience and interview performance.

Work Location

Bangalore, Hyderabad

Hybrid

Yes

BGV Pre/Post onboarding

Pre

If it's pre-onboarding, Interim or final BG report

Final BG Report