Dice is the leading career destination for tech experts at every stage of their careers. Our client, SATCON Inc, is seeking the following. Apply via Dice today! 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: • 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. • 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 • 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. • 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. • 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. • 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. • 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. • 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. • 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