Member of Technical Staff, Software Engineer

The Role

We seek experienced software engineers to build the applications, platforms, tooling, and infrastructure that make every team at Inception more productive. You'll own and drive customer use cases, build product features, development environments, and internal tools — that directly accelerate our ability to bring the latest AI technology to our customers. This role is ideal for engineers who care deeply about customer experience and developer velocity and want to work at a company where the software you build is a force multiplier on a world-class research and engineering org.

• Develop new product features to unlock new customer use cases.
• Create and maintain development environments, tooling, and workflows that improve developer velocity.
• Build internal tools and dashboards for experiment tracking, resource management, and operational visibility.
• Establish and promote engineering best practices around testing, code review, release management, and incident response.
• Collaborate across research, ML infrastructure, and product teams to understand pain points and prioritize high-impact improvements.

• BS/MS/PhD in Computer Science or a related field (or equivalent experience).
• 5+ years of experience in software engineering, application development, developer tooling, platform engineering, Dev Ops, or infrastructure roles.
• Strong proficiency in Python; comfort with at least one systems language (Go, Rust, C++) is a plus.
• Experience working with modern software development (CI/CD systems, Git Hub Actions, Jenkins, Build Kite) and deployment automation.
• Familiarity with Kubernetes, Docker, and container orchestration in production environments.
• Experience with infrastructure as code and cloud platforms (AWS, Azure).
• A strong empathy for customer experience and developer velocity — you care deeply about bringing AI to customers and about making other engineers' lives easier.

• Experience developing AI/ML-powered product features that are loved by customers.
• Experience building and operating ML or GPU-intensive workloads (training clusters, inference pipelines, serving APIs, large artifact management).
• Familiarity with monitoring and observability stacks.
• Experience with testing strategies for ML systems (nondeterminism, regression testing, evaluation-driven validation).
• Experience scaling developer tooling at a fast-growing startup or engineering organization.