AWS Sagemaker
Actively Reviewing the ApplicationsPeople Prime Worldwide
Job Description
About Client :-
Our client is a French multinational information technology (IT) services and consulting company, headquartered in Paris, France. Founded in 1967, It has been a leader in business transformation for over 50 years, leveraging technology to address a wide range of business needs, from strategy and design to managing operations.
The company is committed to unleashing human energy through technology for an inclusive and sustainable future, helping organizations accelerate their transition to a digital and sustainable world.
They provide a variety of services, including consulting, technology, professional, and outsourcing services.
Job Details:-
location : Pan India
Mode Of Work : Hybrid
Notice Period : Immediate Joiners
Experience : 8-10yrs
Type Of Hire : Contract to Hire
Job Description
Design, develop, and deploy intent classification and intent detection models using LLMs and traditional NLP methods.
· Build and optimize Natural Language Generation (NLG) pipelines for chatbot responses, summarization, content creation, or knowledge grounding.
· Architect and implement LangChain and LangGraph based applications for LLM-driven workflows (e.g., autonomous agents, RAG systems).
· Develop scalable machine learning pipelines using the AWS tech stack (e.g., Sagemaker, Lambda, Bedrock, Step Functions, DynamoDB, Athena).
· Integrate and fine-tune foundation models via AWS Bedrock, including Amazon Titan, Anthropic Claude, or Meta Llama.
· Collaborate closely with product managers, ML researchers, and backend engineers to translate business requirements into robust AI solutions.
· Lead experimentation efforts, conduct A/B testing, and ensure continuous evaluation of deployed ML models.
· Mentor junior ML engineers and contribute to best practices in MLOps, model governance, and responsible AI.
Required Qualifications:
· Experience in machine learning, with a focus on NLP and Generative AI.
· Strong experience building and deploying intent detection, text classification, sequence tagging, and entity recognition models.
· Proficient in LangChain, LangGraph, vector databases (e.g., FAISS, Pinecone), and orchestration of LLM workflows.
· Deep knowledge of AWS Bedrock, Amazon SageMaker, Lambda, DynamoDB, Step Functions, etc.
· Experience working with open-source LLMs (LLaMA, Mistral, Falcon) or commercial APIs (Claude, GPT-4, etc.).
· Proficient in Python, with a solid grasp of ML frameworks such as PyTorch, HuggingFace Transformers, scikit-learn.
· Strong understanding of MLOps practices including model versioning, CI/CD for ML, monitoring, and auto-scaling.
· Bachelor’s or Master’s in Computer Science, Data Science, or a related field
Required Skills
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