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Generative AI Engineer

Jobs via Dice, Jackson, Mississippi, United States, 39200

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1 day ago Be among the first 25 applicants Get AI-powered advice on this job and more exclusive features. Dice is the leading career destination for tech experts at every stage of their careers. Our client, INNOVIT USA INC, is seeking the following. Apply via Dice today!

W2 Candidates Only

Location:

USA

Visa:

Open to any visa type

with valid work authorization in the USA

Experience Required:

6 to 12 years

Level:

Mid to Lead positions

Responsibilities:

Architect, develop, and optimize generative AI models including large language models (LLMs) for diverse enterprise use cases. Research and prototype advanced generative AI techniques (e.g., transformers, diffusion models, RAG, LoRA). Collaborate with data scientists, MLOps teams, and product stakeholders to align generative AI initiatives with business objectives. Implement fine-tuning, prompt engineering, and model distillation techniques for performance optimization. Integrate generative models into real-time applications and large-scale production pipelines. Drive the evaluation of open-source and commercial LLMs for cost, performance, and compliance. Create reusable components and APIs for LLM access, tool use, agentic orchestration, and generative tasks. Ensure fairness, interpretability, and safety across all deployed GenAI applications.

Qualifications:

6+ years of experience in AI/ML; 3+ years in building generative AI systems. Hands-on experience with Hugging Face Transformers, LangChain, OpenAI APIs, and vector DBs like Pinecone or FAISS. Strong Python programming, including experience with PyTorch or TensorFlow. Solid understanding of agentic frameworks (CrewAI, LangGraph) and orchestration tools. Prior deployment experience on cloud platforms such as Azure, AWS, or Google Cloud Platform. Knowledge of containerization (Docker, Kubernetes) and model lifecycle management (MLflow, Weights & Biases). Familiarity with responsible AI, prompt injection mitigation, and safe model usage principles

Seniority level

Seniority level Mid-Senior level Employment type

Employment type Full-time Job function

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