Urgent Needed - GenAI/ML Engineer

Hi,

Our Client is looking for GenAI/ML Engineer for Charlotte, NC. If you are looking for a job change, please let me know.

GenAI/ML Engineer

Charlotte, NC Hybrid

24+ Months of Contract Role

Job Description

Role: Al Platform Lead Engineer - GenAl & Agentic Al- No of Positions 2 (Onshore)

Key Responsibilities:

1) Platform Engineering

• Design and build scalable, modular GenAl platforms to support data science and ML workflows.
• Architect end-to-end pipelines for model training, fine-tuning, inference, and evaluation.
• Lead the development of Agentic Al platforms that support autonomous agents, tool use, memory, and planning.

2) GenAl Model Integration

• Integrate and operationalize LLMs (e.g., GPT, Mistral, LLaMA) and multimodal models.
• Enable prompt engineering, fine-tuning (LoRA, PEFT), and RAG (Retrieval-Augmented Generation).
• Build reusable APIs and SDKs for model orchestration and experimentation.
• Al/Gen Al initiative to build GEN Al data science platform to provide E2E capability for model development lifecycle with integrated big c
• Strong Hands on experience in OpenAI, Llama3, H2O, Python, R, Spark, PySpark, ONNX on HPC (HP Compute Cluster [GPU]) platform

3) API Development & Service Layer

• implement robust RESTful APIs using FastAPI or similar frameworks.
• Ensure secure, scalable, and low-latency endpoints for model inference and data access.
• Enable API-based access to GenAl capabilities for internal and external consumers.

4) Vector Database & Semantic Search

• Integrate and manage Vector Databases (e.g., FAISS, Pinecone, Radis Chroma) for semantic search and RAG pipelines.
• Optimize vector indexing, retrieval performance, and hybrid search strategies.
• Support document ingestion, chunking, embedding generation, and metadata tagging.

5) Collaboration with Data Scientists

• Provide self-service tools and environments (e.g., JupyterHub, MLFlow, LangChain) for rapid experimentation.
• Translate data science needs into platform features and enhancements.
• Offer training, documentation, and support for platform adoption.

6) MLOps & DevOps Enablement

• Implement CI/CD pipelines for GenAl model lifecycle management.
• Automate model deployment, monitoring, rollback, and versioning.
• reproducibility, traceability, and governance of Al assets.

7) Security, Compliance & Responsible Al

• Enforce data privacy, access control, and ethical Al practices.
• Integrate tools for explainability, bias detection, and audit logging.
• Alion platform capabilities with enterprise compliance and regulatory standards Internal Companywide usage.

8) Performance Optimization

• Optimize compute resource usage (e.g., GPU/TPU scheduling, quantization, batching).
• Benchmark model performance and latency across deployment environments.
• Implement caching and streaming for real-time GenAl applications.

9) Innovation & Roadmap Leadership

• Stay ahead of GenAl and Agentic Al trends, tools, and frameworks.
• Evaluate and integrate emerging technologies (e.g., LangGraph, AutoGen, CrewAl).
• Define and drive the platform roadmap in alignment with business and Al strategy.

Thanks and Regards

Sai Kishor