Senior Backend Engineer (Machine Learning Infrastructure)

Member of Technical Staff, Backend

Location: San Francisco, CA

Work Policy: 5 days per week in-office

Compensation: $200K to $325K base + bonus + stock

Visa: Sponsorship and transfers available

About the Role

A fast-growing AI company is hiring backend engineers to build the core systems behind its machine learning platform.

This is a high-ownership engineering role focused on taking ML capabilities from experimentation into reliable production systems.

You will work across backend architecture, ML inference, data pipelines, APIs, monitoring, application logic, and customer-facing systems.

The team is small, experienced, and moving quickly, with significant engineering growth planned.

What You’ll Do

• Build backend systems supporting ML training and production inference
• Design services that connect LLMs, ML models, application logic, and customer workflows
• Build scalable pipelines for extracting and structuring complex data
• Develop APIs and database layers supporting customer-facing products
• Integrate external APIs and third-party data sources
• Build monitoring and observability around production ML systems

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• Improve scalability, reliability, and performance
• Drive architectural decisions across core services
• Improve CI/CD and engineering velocity
• Work directly with users to understand requirements and translate them into technical solutions
• Own problems end to end rather than working within a narrow engineering function

What They’re Looking For

• 4+ years of backend software engineering experience
• Strong Python experience
• Experience building production systems at a strong engineering organization
• Experience working with large or complex datasets
• Strong distributed systems or data pipeline experience
• Exposure to production ML systems, inference infrastructure, or AI applications
• Experience with AWS or GCP
• Familiarity with Kubernetes, Docker, Postgres, Redis, or object storage
• Strong product judgement and pragmatic technical decision-making
• Comfortable working directly with customers and non-engineering stakeholders
• Evidence of progression, increasing ownership, or technical leadership
• Comfortable working in-office five days per week in San Francisco

Strong Background Signals

Particularly relevant experience includes:

• Backend engineering at a high-bar technology company or well-funded startup
• Python-heavy production systems
• Large-scale data ingestion or processing
• ML inference or model integration
• Distributed systems
• Cloud infrastructure
• Kubernetes
• Customer-facing engineering
• Startup or high-growth environments

Why Consider It

You would join a small engineering team where individual contributors have significant influence over architecture, technical standards, and product direction.

The work sits directly between machine learning systems and real production use cases, with engineers responsible for making AI capabilities reliable, scalable, and useful.

The company has substantial backing, strong hiring plans, and the resources to scale while maintaining a fast-moving engineering environment.

Compensation

Base salary: $200K to $325K

Additional compensation: Bonus + stock

Final compensation depends on experience, technical depth, and level.