Staff AI/ML Engineer - AI Foundation & Production

We Love AI Jobs; New York, Northern (NY, KY); Hybrid; USD 270,000 - 305,000; Full time

Benefits offered by this job

Stock options

Health benefits

Flexible time off

Job summary

Sigma Computing is seeking a Staff AI/ML Engineer to build the AI foundation for its data analytics platform in New York City. You will partner with product, design, and engineering teams to prototype and productionize AI systems, including recommendations, natural-language interfaces, and agentic workflows.

You will also develop and scale AI/ML infrastructure powering internal tools and customer-facing features, tackling complex ML problems end-to-end in a fast-moving environment.

Qualifications

• 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.

Responsibilities

• Identify high-impact AI/ML opportunities with product, design, and engineering teams.
• Prototype and productionize AI systems such as recommendations, natural-language interfaces, and agentic workflows.
• Develop and scale AI/ML infrastructure for internal tools and customer-facing features.
• Collaborate with cross-functional teams to drive AI-forward roadmaps.

Skills

Machine learning

Deep learning

Applied AI

Foundation model adaptation

Data curation

Model training

Model deployment

Model monitoring

Cloud platforms (AWS, GCP, Azure)

Education

Bachelor's Degree

Tools

AWS

GCP

Azure

Job description

Sigma Computing is seeking a Staff AI/ML Engineer to build the AI foundation for its data analytics platform in New York City. You will partner with product, design, and engineering teams to prototype and productionize AI systems, including recommendations, natural-language interfaces, and agentic workflows.

You will also develop and scale AI/ML infrastructure powering internal tools and customer-facing features, tackling complex ML problems end-to-end in a fast-moving environment.