AI Research Scientist/Engineer

ZipRecruiter; Menlo Park (CA); On-site; USD 180,000 - 200,000; Full time

Job summary

A leading AI startup in Menlo Park is seeking an AI Research Scientist/Engineer to innovate and design novel LLM architectures with a focus on diffusion methods. This role involves collaboration with top researchers and turning complex research into production-ready systems. Candidates should have a PhD in a related field, experience in machine learning, and a strong foundation in AI research. Join a dynamic team dedicated to pushing the limits of generative AI.

Qualifications

• PhD in Computer Science, Machine Learning, or a related field.
• Hands-on experience with PyTorch and LLM fundamentals.
• Solid research-to-production mindset with 2+ years in an ML/AI role.

Responsibilities

• Design and refine LLM architectures built on a diffusion-first paradigm.
• Develop cutting-edge training strategies and custom loss functions.
• Translate research into real-world systems for enterprise-scale deployments.

Skills

Machine Learning

PyTorch

Model Efficiency

Education

PhD in Computer Science or related field

Tools

vLLM

TensorRT

Job description

Job DescriptionJob DescriptionAI Research Scientist/Engineer

Menlo Park, CA | On-Site | Full-Time/Direct Hire

Client Opportunity | Through Phizenix (WBENC & Minority-Certified Recruiting Partner)

Join a trailblazing AI startup that's reinventing how large models are built—with diffusion-powered LLMs that generate faster, adapt smarter, and handle multimodal data like no other.

We're looking for a Research Scientist / Engineer who's ready to move beyond traditional autoregressive methods and help shape the next wave of generative AI. You'll collaborate with pioneers in AI research, design novel model architectures, and scale your ideas from paper to production.

What You'll Be Doing

• Design and refine LLM architectures built on a diffusion-first paradigm

• Develop cutting-edge training strategies and custom loss functions

• Translate research into real-world systems for enterprise-scale deployments

• Explore constraint-aware and controlled outputs

• Push the limits of model efficiency, scalability, and multi-modal capabilities

Must-Haves

• PhD in Computer Science, Machine Learning, or a related field

• Hands-on experience with PyTorch and LLM fundamentals (transformers, KV caching, etc.)

• Familiarity with diffusion models and distributed model training

• Solid research-to-production mindset with 2+ years in an ML/AI role

Bonus Points For

• Training LLMs from scratch and optimizing large-scale runs

• Advanced training tactics (e.g., mixed precision, gradient accumulation)

• Experience with cross-modal modeling and inference frameworks like vLLM, TensorRT

• A background in model efficiency, optimization theory, or infrastructure-aware research

At Phizenix, we're proud to partner with diverse and inclusive teams building AI that matters. If you're ready to build, innovate, and publish with one of the boldest teams in AI—this is your moment.

California Pay Range$180,000—$200,000 USD