Member of Technical Staff, Backend, LLM Applications
Palo Alto, CAFull-timePosted 6mo agoStill listed 3 days ago
Most applications go out cold — see where you stand first. No sign-up to start.
Watch jobs like this. New roles like this one near Palo Alto, CA, by email.
Don't just apply. Show up ready.
Olive works from this exact posting.
At a glance
Olive lists jobs from US employers, including remote roles you can work from the United States.
Requirements
Credentials this posting asks for.
Job overview
Inception Labs seeks experienced backend engineers to design, build, and operate scalable backend services and model serving infrastructure for diffusion LLMs, focusing on latency, throughput, cost, and reliability, while collaborating with world‑class AI researchers in a fast‑growing startup environment.
Skills & qualifications
Skills
Qualifications
Benefits
Full job description
Member of Technical Staff, Backend, LLM Applications Bay Area
Platform
In office
Full-time
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 Role We seek experienced backend engineers to own the systems that serve our diffusion LLMs in production. You'll build and operate infrastructure that handles billions of inference requests — optimizing for latency, throughput, cost, and reliability. This role sits at the intersection of ML systems and backend infrastructure.
Key Responsibilities
- Design, build, and operate scalable backend services and model serving infrastructure for our diffusion LLMs.
- Implement and manage load balancing, autoscaling, and traffic routing for model endpoints.
- Build systems for model versioning, canary deployments, and zero-downtime rollouts.
- Develop monitoring, alerting, and observability tooling to ensure SLA compliance and rapid incident response.
- Benchmark and evaluate serving frameworks and hardware configurations to inform infrastructure decisions.
Qualifications
- BS/MS/PhD in Computer Science or a related field (or equivalent experience).
- 5+ years of experience building production backend systems.
- Strong proficiency in Python, including async programming and concurrent systems.
- Solid understanding of distributed systems, networking, and load balancing at scale.
- Familiarity with Kubernetes, CI/CD pipelines, and cloud infra (AWS and/or Azure).
Preferred Skills
- Experience serving LLMs or other large generative models in production at scale.
- Experience with cloud infrastructure (AWS, Azure), including GPU instance management and cost optimization.
- Experience with infrastructure as code tools (Terraform) and deployment automation.
- Experience with monitoring and observability tools (Prometheus, Grafana).
- Familiarity with model serving frameworks (vLLM, Triton Inference Server, TensorRT-LLM).
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
- Catered meals (breakfast, lunch, & dinner)
- Commuter subsidies
- A collaborative and inclusive culture
About Us Inception 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 Google DeepMind, Meta AI, Microsoft AI, and OpenAI. Based in Palo Alto, CA, we are backed by A-list 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.
Ready to apply? Powered by
First name *
Last name *
Email *
LinkedIn URL
Resume * Click to upload or drag and drop here
Req ID: R38
Similar jobs, posted recently
Open roles like this one, listed in the last 30 days.
Member of Technical Staff - Engineering Lead, ApplicationsReflection AI · San Francisco, CAPosted 2 days agoPosted 2 days agoMember of Technical Staff, FrontendVapi · San Francisco, CA (Hybrid) · $235–264K/yrPosted 1w agoPosted 1w ago
Member of Technical Staff, Product SecurityParallel · Bay Area, CA · $150–300K/yrPosted 2w agoPosted 2w agoMember of Technical Staff, Infrastructure EngineerVapi · San Francisco, CA (Hybrid) · $280–314K/yrPosted 2w agoPosted 2w ago
Member of Technical Staff, EvalsHandshake · San Francisco, CA · $200–350K/yrPosted 3 days agoPosted 3 days ago
You've read the whole posting — now see how you match it.