- Company Name
- Enzo Tech Group
- Job Title
- Data Scientist
- Job Description
-
Job Title: Data Scientist – ML / GenAI / Agentic AI
Role Summary:
Develop, deploy, and maintain machine‑learning models, generative‑AI solutions, and agentic‑AI workflows to enhance forecasting, optimization, personalization, and automation for a Fortune 500 food & beverage business. Collaborate with cross‑functional teams and deliver actionable insights to technical and non‑technical stakeholders.
Expectations:
- Remote, USA‑based contract; adhere to company timelines and deliverables.
- Demonstrate strong communication skills to present model outcomes and AI benefits to diverse audiences.
- Ensure high‑quality, production‑ready models and robust MLOps pipelines.
Key Responsibilities:
1. Build and deploy machine‑learning models for forecasting, optimization, and personalization.
2. Fine‑tune large language models (LLMs) and develop generative‑AI applications involving Retrieval‑Augmented Generation (RAG), embeddings, and multimodal capabilities.
3. Design and implement agentic‑AI workflows (e.g., LangChain agents, AutoGen, ReAct) to automate complex business processes.
4. Partner with cross‑functional teams to identify high‑impact AI use cases and translate business requirements into technical solutions.
5. Manage end‑to‑end MLOps lifecycle: model training, validation, versioning, deployment, monitoring, and maintenance using cloud platforms.
6. Present technical findings, model performance metrics, and ROI analyses to stakeholders.
Required Skills:
- Programming: Python, SQL.
- ML/AI frameworks: PyTorch, TensorFlow, scikit‑learn.
- GenAI expertise: LLM fine‑tuning, RAG, vector databases, embeddings.
- Agentic AI: LangChain Agents, AutoGen, ReAct‑style frameworks.
- MLOps & Cloud: AWS, Azure, GCP, MLflow, Databricks, SageMaker, Vertex.
- Strong analytical and statistical problem‑solving abilities.
- Proven experience in deploying production‑grade ML/AI pipelines.
- Excellent cross‑functional collaboration and communication skills.
Required Education & Certifications:
- Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or related technical field.
- Professional certifications in cloud (AWS/Azure/GCP) or MLops/Deep Learning are advantageous.