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Clera

Founding Machine Learning Engineer

Clera · $220K–$300K/yr

Technology, Information and Internet · 2-10 employees

Yesterday
Senior (5-10 yrs) Full-time
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About the role

You will design, train, and deploy production-grade machine learning systems while building end-to-end pipelines from data ingestion to inference. Additionally, you will collaborate with cross-functional teams to establish best practices in model versioning, reproducibility, and continual learning.

What they look for

Python PyTorch TensorFlow JAX LLMs Machine Learning Pipelines Distributed Training Inference Systems Generative Models MLflow Weights & Biases Cloud Platforms Data Ingestion Model Evaluation Scalable Systems

Requirements

Candidates must have 3–10 years of hands-on experience as an ML Engineer or Applied Scientist with proficiency in Python and deep learning frameworks. You must also possess proven experience in building scalable, production-grade ML systems and have existing US work authorization.

Benefits

Equity participation Founding team member status Technical leadership opportunity

Full description

About the Role

This is a founding-level, hands-on ML engineering role at a fast-growing Series A AI startup in the Bay Area, specializing in high-quality training data, post-training data pipelines, and model evaluation for frontier AI labs and enterprises. You'll work closely with leadership to design, train, and ship production-grade ML systems — while helping shape the technical culture and infrastructure from the ground up.

This role is fully on-site in Mountain View, CA. Candidates must be authorized to work in the US without visa sponsorship.

What You'll Do

  • Build and optimize end-to-end ML pipelines, from data ingestion through to production deployment.
  • Implement and fine-tune LLMs, embeddings, and generative models for real-world applications.
  • Develop efficient training and inference systems leveraging distributed compute at scale.
  • Partner with data and product teams to translate ideas into measurable ML impact.
  • Contribute to model monitoring, evaluation, and continual learning frameworks.
  • Establish best practices in model versioning, reproducibility, and scalability across the organization.

What We're Looking For

Required

  • 3–10 years of hands-on experience as an ML Engineer, Applied Scientist, or Research Engineer.
  • Proficiency in Python and at least one of PyTorch, TensorFlow, or JAX.
  • Proven experience building production-grade, end-to-end ML pipelines (data ingestion, training, deployment).
  • Experience implementing and fine-tuning LLMs, embeddings, and generative models for real-world use cases.
  • Hands-on experience with distributed training/inference and scalable ML systems.
  • Familiarity with cloud platforms (AWS, GCP, or Azure) and ML tooling such as MLflow or Weights & Biases.
  • Strong collaboration skills with cross-functional data and product teams.
  • Bias for action, ability to work autonomously, and eagerness to build from scratch.

Nice to Have

  • Experience with RL environments or evaluation frameworks for AI models.
  • Background in agentic systems, tool-use pipelines, or multi-step execution trajectories.
  • Prior experience at an early-stage startup or in a founding-engineer capacity.

Compensation & Benefits

  • Salary: $220,000 – $300,000 per year, depending on experience.
  • Equity participation as a founding team member.
  • Opportunity to directly shape technical direction, culture, and hiring at an early-stage, high-growth company.

Location

  • On-site in Mountain View, California.
  • No visa sponsorship available — candidates must have existing US work authorization.