Applied AI and Machine Learning Director
On-site · Wilmington, Delaware, United States
Job Summary
Applied AI and Machine Learning Director leads and grows a data science team, guiding end-to-end GenAI/AI/ML use-case delivery from ideation to production, mentoring team members, establishing best practices, and collaborating with engineering, product, and business teams to translate needs into plans, success metrics, and shipped capabilities. Responsibilities include hands-on contribution to solution architecture and code reviews, designing GenAI solutions with large language models and agentic AI, building scalable data pipelines and ETL/ELT processes, partnering with engineering to deliver robust solutions, aligning requirements with business impact, defining project plans and success metrics, and communicating progress and risks to senior leaders. Required capabilities include advanced Python, GenAI delivery with LLMs, LangChain/LlamaIndex/AutoGen/CrewAI, retrieval augmented generation, embeddings/vector databases, modern data platforms (Snowflake/Databricks, cloud), ML libraries (pandas, NumPy, scikit-learn, PyTorch, TensorFlow), MLOps practices, and demonstrated leadership and delivery in enterprise AI initiatives. A bachelor’s degree in relevant fields or equivalent practical experience is required.
Required Qualifications
- Bachelor’s degree in Computer Science, Engineering, Data Science, Mathematics, Statistics, or equivalent practical experience
- Advanced Python programming skills with production-quality, maintainable code
- Hands-on experience delivering GenAI solutions using large language models (prompt engineering and fine-tuning)
- Experience with agentic AI frameworks such as LangChain, LlamaIndex, AutoGen, or CrewAI
- Experience with retrieval augmented generation patterns, embeddings, vector search, and vector databases
- Experience with modern data platforms and ETL/ELT practices (e.g., Snowflake, Databricks, cloud platforms)
- Experience with common data science libraries (pandas, NumPy, scikit-learn, PyTorch, TensorFlow)
- Working knowledge of MLOps (model versioning, experiment tracking, deployment pipelines, Git, containerization)
- Proven people leadership and delivering AI/ML initiatives in large enterprise environments
- Strong project and stakeholder management across cross-functional teams
- Bachelor’s degree in Computer Science, Engineering, Data Science, Mathematics, Statistics, or equivalent practical experience
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