Sigma Computing is seeking a Staff AI/ML Engineer to lead the development of advanced machine learning models that power our innovative data analytics platform. Join a dynamic team to push the boundaries of AI-driven insights and scalability in cloud environments.

About Sigma Computing

Sigma Computing is a fast-growing data analytics platform that empowers teams to build powerful, interactive dashboards and workflows without coding. We're at the forefront of transforming how businesses leverage data with AI and ML innovations.

The Role

As a Staff AI/ML Engineer, you'll be a key contributor to our AI team, architecting and implementing machine learning solutions that enhance our platform's capabilities in automated insights, predictive analytics, and natural language processing. You'll work closely with product managers, data scientists, and backend engineers to deliver high-impact features that scale to millions of users.

Key Responsibilities

• Lead the end-to-end development of ML models, from ideation to production deployment
• Optimize algorithms for performance, accuracy, and efficiency in distributed systems
• Collaborate on integrating ML into our core platform, ensuring seamless user experiences
• Mentor junior engineers and drive best practices in MLOps and experimentation
• Stay ahead of emerging AI trends and evaluate new technologies for adoption
• Contribute to open-source projects and represent Sigma at industry conferences

Why Join Us?

At Sigma, you'll work with a passionate team in a high-growth environment backed by top-tier investors. We value innovation, ownership, and work-life balance, offering opportunities to make a real difference in the data analytics space.

• 8+ years of experience in machine learning engineering, with a focus on production-grade ML systems
• Expertise in Python, TensorFlow, PyTorch, or similar frameworks
• Strong background in designing and deploying scalable ML pipelines using tools like Kubeflow, Airflow, or MLflow
• Proficiency in data processing with Spark, Pandas, or Dask
• Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes)
• Deep knowledge of model optimization, feature engineering, and MLOps practices
• Bachelor's or Master's degree in Computer Science, Statistics, or related field
• Excellent problem-solving skills and ability to collaborate cross-functionally

• Competitive monthly salary with performance bonuses
• Comprehensive health, dental, and vision insurance
• Flexible remote work arrangement with home office stipend
• Generous paid time off and parental leave
• Stock options and 401(k) matching
• Professional development budget for conferences and courses
• Access to state-of-the-art tools and cutting-edge AI technologies
• Collaborative and inclusive company culture with team-building events