Lead Machine Learning Engineer - Generative AI - 1584

aKube • Burbank, CA

8h • Hybrid

About The Position

Design and build GenAI and LLM -based prototypes and MLPs
Develop chatbots, copilots, summarization, and automation workflows
Implement and evaluate RAG, embeddings, and LLM techniques
Build PoCs using modern ML frameworks and cloud -native tools
Support experiment design, benchmarking, and model evaluation
Collaborate with product, data, and engineering teams
Contribute to architecture discussions and technical decisions
Apply MLOps best practices and support documentation and demos

Requirements

• 6+ years in software engineering or ML/AI engineering
• 2+ years hands -on with GenAI, LLMs, or advanced ML platforms
• Python expertise and production ML system development
• Experience with PyTorch, TensorFlow, HuggingFace, LangChain
• Hands -on work with RAG pipelines, embeddings, prompt engineering, LLM fine -tuning
• Experience with AWS, Azure, or GCP deployments
• Experience with NoSQL, relational, and vector databases
• MLOps tools: MLflow, Docker, Kubernetes

Nice To Haves

• Experience in R&D or innovation -focused teams
• Background building internal AI/ML platforms or tooling
• Open -source contributions, patents, or ML publications

Responsibilities

• Design and build GenAI and LLM -based prototypes and MLPs
• Develop chatbots, copilots, summarization, and automation workflows
• Implement and evaluate RAG, embeddings, and LLM techniques
• Build PoCs using modern ML frameworks and cloud -native tools
• Support experiment design, benchmarking, and model evaluation
• Collaborate with product, data, and engineering teams
• Contribute to architecture discussions and technical decisions
• Apply MLOps best practices and support documentation and demos

What This Job Offers

• Career Level: Mid Level