Member of Technical Staff, ML Product Engineer

Inception; San Francisco (CA); On-site; USD 200,000 - 350,000; Full time

Benefits offered by this job

Equity

Health insurance

Dental insurance

Vision insurance

Flexible PTO

Catered meals

Career growth

Job summary

Inception is seeking experienced engineers and researchers to bridge research and real-world application of diffusion LLMs. You will design, train, and deploy models at scale, collaborate with customers to translate their needs into technical solutions, and ensure reliability in production environments.

You will work with cutting-edge tech, from diffusion models to MLOps, and join a fast-growing team in Palo Alto, CA, with competitive compensation, equity, flexible PTO, and comprehensive health

Qualifications

• BS/MS/PhD in Computer Science, Machine Learning, or a related field (or equivalent experience).
• At least 5 years of experience working on ML projects in PyTorch (or equivalent).
• Excellent familiarity with transformers and core LLM concepts (autoregressive pretraining, instruction tuning, in-context learning, LoRA, KV caching).
• Experience training LLMs, including fine-tuning.
• Familiarity with large-scale systems and high-performance computing, including GPU/TPU utilization.
• Experience with version control (Git) and containerization (Docker).
• Excellent communication skills with the ability to explain technical concepts to non-technical stakeholders.

Responsibilities

• Design, develop, and optimize our models for production use cases.
• Partner with customers to understand their requirements and translate them into technical solutions.
• Implement innovative approaches for post-training generative AI models, including agentic workflows.
• Work on data preprocessing pipelines, model evaluation, and alignment to enterprise use cases.
• Contribute to the deployment and maintenance of models in production environments.
• Collaborate with product teams to design and implement customer-facing ML features.

Skills

PyTorch

Transformers

LLM concepts

Model training

Production systems

Communication skills

GPU/TPU usage

Education

BS/MS/PhD in Computer Science/ML or related field

Tools

Docker

Git

vLLM

TensorRT

Kubernetes

Job description

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 engineers and scientists to bridge the gap between research and real-world applications by training and deploying our diffusion large language models. You'll build our core product offerings, partner with customers, and ensure our models perform reliably at scale in production environments.

Key Responsibilities

• Design, develop, and optimize our models for production use cases.
• Partner with customers to understand their requirements and translate them into technical solutions.
• Implement innovative approaches for post-training generative AI models, including agentic workflows.
• Work on data preprocessing pipelines, model evaluation, and alignment to enterprise use cases.
• Contribute to the deployment and maintenance of models in production environments.
• Collaborate with product teams to design and implement customer-facing ML features.

Qualifications

• BS/MS/PhD in Computer Science, Machine Learning, or a related field (or equivalent experience).
• At least 5 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, LoRA, KV caching).
• Experience training LLMs, including fine-tuning.
• Familiarity with large-scale systems and high-performance computing, including GPU/TPU utilization.
• Experience with version control (Git) and containerization (Docker).
• Excellent communication skills with the ability to explain technical concepts to non-technical stakeholders.

Preferred Skills

• Expertise in data engineering and synthetic data generation for LLMs.
• Knowledge of MLOps and production-level deployment workflows.
• Experience with LLM serving frameworks like vLLM, SGLang, or TensorRT.
• Experience with cloud platforms (AWS, GCP, Azure).
• Experience with model quantization and optimization techniques.

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
• 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)
• 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 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.