Founding Engineer – ML Research

Clera; United States; On-site; USD 220,000 - 300,000; Full time

Job summary

Clera in Mountain View, CA seeks a Founding ML Research Engineer to help build the AI research backbone from the ground up. This role blends applied ML with systems engineering and thrives in unstructured environments.

You will design and train models (LLMs, diffusion, RLHF), build scalable experiment pipelines, and deliver production-ready tools. Work directly with the founding team to push frontier AI with rigorous accuracy and reproducibility.

Qualifications

• 3–10 years of hands-on ML research or ML systems engineering.
• Proficiency in Python and ML frameworks: PyTorch, JAX, and/or TensorFlow.
• Experience with Transformers, Diffusion Models, and RLHF techniques.
• Proven ability to design and build scalable experimentation pipelines for data, model, and evaluation workflows.
• Track record contributing to open research or multimodal/generative AI techniques.

Responsibilities

• Design, train, and evaluate ML models including LLMs, diffusion models, and domain-specific architectures.
• Develop scalable experimentation pipelines covering data, model, and evaluation workflows.
• Collaborate with data and infrastructure teams to optimize training throughput and model quality.
• Contribute to open research, internal benchmarks, and emerging techniques in multimodal and generative AI.
• Rapidly prototype and productionize research insights into usable tools and production-ready models.
• Define foundational technical culture—standards for research rigor, documentation, and reproducibility.

Tools

PyTorch

JAX

TensorFlow

Transformers

Diffusion models

RLHF

ML research

Python

Experiment pipelines

Documentation

Job description

About the Role

A well-funded, Series A/B AI startup headquartered in Mountain View, CA - working with some of the world's top frontier AI labs - is looking for a Founding ML Research Engineer to help build and scale their AI research backbone from the ground up.

This role sits at the intersection of applied machine learning and systems engineering. It's ideal for someone who thrives in unstructured environments, loves building fast, and obsesses over model performance and data quality. You'll work directly with the founding team to prototype, experiment, and ship research-driven features that push the boundaries of cutting-edge AI systems.

The company specializes in high-quality training and post-training data, robust RL environments, and intelligent agents for frontier AI labs and enterprises - with a strong emphasis on accuracy, safety, and reliability.

No visa sponsorship is available. Candidates must have current eligibility to work in the United States.

What You'll Do

• Design, train, and evaluate ML models including LLMs, diffusion models, and domain-specific architectures.

• Develop scalable experimentation pipelines covering data, model, and evaluation workflows.

• Collaborate closely with data and infrastructure teams to optimize training throughput and model quality.

• Contribute to open research, internal benchmarks, and emerging techniques in multimodal and generative AI.

• Rapidly prototype and productionize research insights into usable tools and production-ready models.

• Define foundational technical culture - establish standards for research rigor, documentation, and reproducibility.

What We're Looking For

Required:

• 3-10 years of hands-on experience in ML research, applied ML, or ML systems engineering.

• Deep proficiency in Python and ML frameworks: PyTorch, JAX, and/or TensorFlow.

• Strong hands-on experience with model architectures including Transformers, Diffusion Models, and RLHF techniques.

• Proven experience designing and building scalable experimentation pipelines for data, model, and evaluation workflows.

• Track record of contributing to open research, internal benchmarks, or emerging multimodal/generative AI techniques.

• Ability to move fluidly from research papers working prototypes production-ready code.

• Strong documentation habits and commitment to reproducibility.

Nice to Have:

• Curiosity for and experience with emerging ML paradigms: multimodality, self-learning, synthetic data, agentic systems, etc.

• Background at an AI-native startup or frontier lab environment.

• Experience setting foundational technical culture in an early-stage team.

Compensation & Benefits

• Base salary: $220,000 - $300,000 per year, depending on experience.

• Equity participation as a founding team member.

• Opportunity to shape research direction and culture from the ground up.

Location

• On-site, full-time in Mountain View, CA. Remote work is not available for this role.

• Must have current authorization to work in the United States - no visa sponsorship provided.