Staff AI/ML Engineer at Sigma Computing

New York, New York, United States

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$240,000 – $270,000Compensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, AI/ML, Business IntelligenceIndustries

Requirements

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

Responsibilities

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

Skills

Key technologies and capabilities for this role

Machine LearningDeep LearningAIML LifecycleData CurationModel TrainingModel DeploymentMonitoringFoundation ModelsRecommendationsNatural Language ProcessingSearchMachine TranslationCloud InfrastructureAWSGCPAzure

Questions & Answers

Common questions about this position

What is the base salary range for the Staff AI/ML Engineer position?

The base salary range is $240k - $270k annually, though compensation may vary based on qualifications, skills, competencies, and experience.

What benefits are offered for this role?

This role is eligible for stock options as well as a comprehensive benefits package, in addition to base pay.

Is this position remote or does it require office work?

This information is not specified in the job description.

What are the key required skills and experience for this role?

Candidates need 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, a track record of shipping complex systems, and experience adapting or training foundation models for novel domains.

What kind of experience stands out for strong candidates?

Strong candidates have a proven track record of shipping production AI/ML systems and experience with the full ML lifecycle, while bonus points go to those who have built AI agents, worked with cloud infrastructure like AWS/GCP/Azure, or thrived in fast-moving startups.

Sigma Computing

Cloud-based data analytics platform for businesses

About Sigma Computing

Sigma Computing offers a cloud-based data analytics platform that enables businesses to analyze large volumes of data through a user-friendly, spreadsheet-like interface. Users can connect to their cloud data warehouse and access advanced features such as data collection, territory management, and revenue planning without needing coding skills. The platform is scalable, allowing for the analysis of billions of rows of data, and promotes self-service capabilities for faster insights. Recently, Sigma introduced AI features like data classification and natural language processing to enhance data analysis and support Enterprise AI initiatives.

San Francisco, CaliforniaHeadquarters

2014Year Founded

$550.9MTotal Funding

SERIES_DCompany Stage

Data & Analytics, AI & Machine LearningIndustries

501-1,000Employees

Benefits

Competitive pay - Looking for a great salary and solid stock options? You’ve come to the right place.

Flexible schedule - Do the work you need to get done in the time you have to get it done

Amazing benefits - Medical, dental, vision, 401k, FSA, commuter… we’ve got you covered. Literally.

Flexible vacation - At Sigma, we work to live, not live to work. So go on, book that dream vacation.

Health & wellness - A healthy body supports a healthy mind, so we partner with Crunch Fitness and CorePower.

Family-friendly - From flexible scheduling to parental leave to kids’ birthdays off, we support Sigma families.

Risks

Competition from Tableau and Power BI could threaten Sigma's market share.

Reliance on platforms like Snowflake may impact service delivery if disruptions occur.

High valuation pressures Sigma to deliver rapid growth, risking strategic misalignment.

Differentiation

Sigma offers a spreadsheet-like interface for non-technical users to analyze data.

The platform integrates with major data warehouses like Snowflake and BigQuery.

Sigma's AI features include natural language processing and sentiment analysis.

Upsides

Sigma raised $200M in Series D funding, valuing it at $1.5 billion.

The platform's scalability allows analysis of billions of data rows efficiently.

Sigma's partnerships enhance data accessibility and integration for users.

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