Staff AI/ML Engineer
Build and productionize AI/ML systems including recommendations, natural language interfaces, and agentic workflows for Sigma's data analytics platform. Requires 10+ years experience across the full ML lifecycle and foundation model expertise.
About the job
What You’ll Do
- Partner with product, design, and engineering teams to identify high-impact AI/ML opportunities
- Prototype and productionize AI systems that feel intuitive but do a lot under the hood—recommendations, natural language interfaces, agentic workflows, and more
- Develop and scale AI/ML infrastructure that powers both internal tooling and customer-facing features
- Tackle novel UX problems at the intersection of AI, BI, and apps
What You Bring
- Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field (required)
- 10+ years of experience building and deploying production-grade AI/ML systems
- Deep knowledge of machine learning, deep learning, and applied AI
- Experience across the full ML lifecycle: data curation, training, deployment, monitoring
- A track record of building things that ship—whether it’s recommendations, search, machine translation, or something equally complex
- Experience adapting or training foundation models (language or multimodal) for novel domains
Bonus Points
- You've built agents that can plan, reason, and use tools
- You know your way around cloud infrastructure (AWS, GCP, Azure)
- You’ve worked in a fast-moving startup or high-growth environment
Compensation
The base salary range for this position is $240k - $270k annually. This role is eligible for stock options, as well as a comprehensive benefits package including equity, generous health benefits, flexible time off, paid bonding time, 401k, commuter and FSA benefits, lunch program, and dog friendly office.
Skills
Machine Learning, Deep Learning, Applied Ai, Foundation Models, LLMs, Ml Lifecycle, Data Curation, Model Training, Model Deployment, Model Monitoring, AWS, GCP, Azure, Agentic Workflows, Natural Language Interfaces
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