Member of Technical Staff, Software Engineer

AI in this role

openaidatabricks

Inception creates the world’s fastest, most efficient AI models. Our Mercury model is the world’s fastest reasoning LLM and first commercially available diffusion LLM, delivering 5x greater speed and efficiency than today’s LLMs, with best-in-class quality.
We are the AI researchers and engineers behind such breakthrough AI technologies as diffusion models, flash attention, and DPO.
The RoleWe 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.
Key Responsibilities

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.

Qualifications

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, DevOps, 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, GitHub Actions, Jenkins, BuildKite) 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.

Preferred Skills

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.

Compensation

The annual base salary range for this role is $200,000 – $350,000 USD. Final compensation is determined based on experience, skills, and qualifications. Equity and benefits are included in the total package.
Why Join Inception

Work with World-Class Talent: Collaborate with the inventors of diffusion models and leading AI researchers
Shape Foundational Technology: Your decisions will influence how the next generation of AI products are built and used
Immediate Impact: Join at the ground floor where your contributions directly shape product direction and company trajectory

Perks & Benefits

Competitive salary and equity in a rapidly growing startup
Flexible vacation and paid time off (PTO)
Health, dental, and vision insurance
401k match
Catered meals (breakfast, lunch, & dinner)
Commuter subsidies
A collaborative and inclusive culture

About UsInception creates the world’s fastest, most efficient AI models. Today’s autoregressive LLMs generate tokens sequentially, which makes them painfully slow and expensive. Inception’s diffusion-based LLMs (dLLMs) generate answers in parallel. They are 5x faster and more efficient, while delivering best-in-class quality.
Inception was co-founded by Stanford professor Stefano Ermon, who co-invented such breakthrough AI technologies as diffusion models, flash attention, and DPO, UCLA professor Aditya Grover, who co-invented node2vec, decision transformers, and d1 reasoning, and Cornell professor and Afresh co-founder Volodymyr Kuleshov, who co-invented MDLM and Block Diffusion.
We pioneered the application of diffusion to language, with world’s first (and only) commercially available dLLM, Mercury. We are currently deploying our large-scale diffusion LLMs at Fortune 500 companies. Diffusion is the technology behind today’s image and video AI, and we’re making it the standard for LLMs as well.
Our team includes engineers from AWS, Google DeepMind, Meta AI, Microsoft, HashiCorp, and OpenAI. Based in Palo Alto, CA, we are backed by top-tier venture capitalists, including Menlo Ventures, Mayfield, M12 (Microsoft’s venture fund), Snowflake Ventures, Databricks, and Innovation Endeavors, and by tech luminaries such as Andrew Ng, Andrej Karpathy, and Eric Schmidt.
If you are talented, innovative, and ambitious, come help us invent the future of AI.We are an equal opportunity employer and encourage candidates of all backgrounds to apply.

How we score this

Member of Technical Staff, Software Engineer at Inception Labs scores 89 out of 100 on AI centrality, which makes it AI Level 4 of 4 (Builds AI) on this board. The level measures how much of the work is AI, not seniority.

Classification

AI Level 4. Building AI systems is the job itself: without AI, the role would not exist.

AI Level 480 to 100
AI Level 360 to 79
AI Level 240 to 59
AI Level 10 to 39

Bands come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

OpenAIDatabricks

Questions you could be asked

What's a project where you used OpenAI hands-on?
Walk me through how you've used Databricks in your day-to-day work.
How would you decide a model or AI system is ready to ship?
Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

List these exact terms on your resume: OpenAI and Databricks. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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