Senior Software Engineer

Role: Senior Software Engineer
Employment Type: Full-time
Location: On-site, Mountain View, CA (5 days/week, limited remote flexibility)
Compensation: $153,000 – $222,000 base salary + equity + benefits

This fast-growing Silicon Valley company builds simulation and infrastructure software for autonomous systems. Its products are widely used by Fortune 500 OEMs, Tier 1 suppliers, and defense organizations to accelerate the safe development, testing, and deployment of autonomy.

Founded in 2017, the company has raised over $350M from top investors (including Andreessen Horowitz and General Catalyst) and is valued above $3.5B. With offices across North America, Europe, and Asia, it’s recognized as a leader in autonomy infrastructure and simulation tooling.

As a Senior Software Engineer on the ML Infrastructure team, you’ll design and scale systems that support the training, evaluation, and deployment of large-scale machine learning workloads. The role blends infrastructure engineering with ML platform design, focusing on reliability, scalability, and developer productivity.

You will collaborate closely with autonomy researchers, simulation experts, and product teams to deliver end-to-end ML solutions powering mission-critical autonomy development.

• Design, build, and scale ML infrastructure for training and evaluation pipelines.

• Develop distributed systems to manage large datasets and compute resources.

• Collaborate with applied ML and autonomy research teams to product ionize new algorithms.

• Optimize workflows for simulation, evaluation, and reinforcement learningp>

• Ensure reliability and performance of infrastructure in production settings.

• Contribute to cross-team initiatives that improve scalability and developer velocity.

• BS, MS, or PhD in Computer Science or related field.

• Strong experience in distributed systems, infrastructure, or ML platforms.

• Proficiency with C++, Python, and modern ML frameworks (e.g., PyTorch, Tensor Flow).

• Familiarity with cloud platforms (AWS, GCP, Azure) and container orchestration (Kubernetes).

• Experience optimizing large-scale training or evaluation systems.

• Strong problem-solving and communication skills.

C++, Python, PyTorch, Tensor Flow, Kubernetes, distributed systems frameworks.

• High technical bar: Work with top engineers and researchers solving complex autonomy and ML infra problems.

• Impactful work: Infrastructure powers the development of safety‑critical autonomous systems used by major industry players.

• Fast‑paced: Startup culture with high ownership expectations; candidates should be comfortable with ambiguity.

• Career acceleration: Exposure to cutting‑edge ML + autonomy problems at scale.

• Competitive compensation ($153K–$222K base + equity).

• Comprehensive benefits package (health, dental, vision, 401k).

• On‑site meals, commuter benefits, and wellness programs.

• Visa sponsorship available.

• Collaborative, in‑office work environment in Mountain View HQ.