Member of Technical Staff, Training

Inception Labs is hiring a Member of Technical Staff, Training in San Mateo, United States. Level rates it ; you can apply on Inception Labs.

Level's read on this job

Builds AI ●●●● is how Level rates this role: the job is building AI systems.
Tools and skills the posting cites include OpenAI, vLLM and PyTorch.
Level classifies it as a lead role.
Level lists 7 other open roles at Inception Labs.

AI in this role

OpenAIvLLMPyTorchDatabricks

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 scientists and engineers with deep expertise in pre-, mid-, and post- training large language models. You will advance our diffusion-based LLM models, developing novel training techniques and pushing the boundaries of parallel token generation.
Key Responsibilities

Design, develop, and optimize architectures for diffusion-based language models.
Implement innovative training objectives and loss functions for discrete diffusion LLMs.
Research and implement techniques for controlled text generation and constraint satisfaction.
Develop methods for multi-modal integration within the diffusion framework.
Improve model efficiency, reduce training time, and optimize inference throughput.
Develop and implement post-training techniques to align and improve model behavior.

Qualifications

BS/MS/PhD in Computer Science or a related field (or equivalent experience).
At least 2 years of experience working on ML projects in PyTorch (or equivalent), preferably in a research lab or engineering role.
Excellent familiarity with transformers and core LLM concepts (autoregressive pretraining, instruction tuning, in-context learning, KV caching).
Familiarity with training and inference in diffusion models.
Experience training deep learning models at scale in distributed computing environments.

Preferred Skills

Extensive experience training transformer-based language models from scratch.
Knowledge of advanced training techniques (mixed precision, gradient accumulation, etc.).
Experience with multi-modal learning and cross-modal architectures.
Background in optimization theory and neural network architecture design.
Experience with LLM serving frameworks like vLLM, SGLang, or TensorRT.

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 rate this

Member of Technical Staff, Training at Inception Labs rates 99 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Member of Technical Staff, Training is an open job at Inception Labs.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in San Mateo, United States.
The job was posted on March 10, 2026.
Seniority: lead.
Applications are handled by Inception Labs. Apply on Inception Labs

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

OpenAIvLLMPyTorchDatabricks

Questions you could be asked

What's a project where you used OpenAI hands-on?
Walk me through how you've used vLLM in your day-to-day work.
What are the limits of PyTorch that you've run into, and how did you work around them?
What's a project where you used Databricks hands-on?
How would you decide a model or AI system is ready to ship?

Adapt your resume

List these exact terms on your resume: OpenAI, vLLM, PyTorch, 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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