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Clera

Founding Engineer - Machine Learning

Clera $220K–$300K/yr

Technology, Information and Internet · 2-10 employees

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

Build and optimize end-to-end machine learning pipelines from data ingestion to deployment for frontier AI models. Collaborate with cross-functional teams to implement LLMs and develop scalable training and inference systems.

What they look for

Python PyTorch TensorFlow JAX Machine Learning LLMs Embeddings Generative Models Distributed Systems Cloud ML Infrastructure AWS GCP Azure MLOps Weights & Biases MLflow

Requirements

Requires 3–10 years of experience as an ML Engineer or Research Engineer with proficiency in Python and major ML frameworks. Candidates must have hands-on experience with distributed systems, cloud infrastructure, and MLOps tools.

Benefits

Early-stage equity Founding team role

Full description

About the Role

This is a rare opportunity to join a Series A AI data and services company as a Founding ML Engineer, working directly alongside the founding team to build and scale core machine learning systems from the ground up. You will bridge research and engineering — designing, training, and shipping production-grade models for top AI frontier labs — while helping shape the company's technical culture and infrastructure.

The company specializes in high-quality training and post-training data, reinforcement learning environments, and intelligent agents that accelerate AI model performance for both frontier labs and enterprises. This is a high-ownership, high-impact role: your work will directly establish the foundation for how the team delivers measurable ML outcomes.

Visa sponsorship is not available for this role.

What You'll Do

  • Build and optimize end-to-end ML pipelines, from data ingestion through to deployment.
  • Implement and fine-tune LLMs, embeddings, and generative models for real-world applications.
  • Develop efficient training and inference systems leveraging distributed compute.
  • 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.

What We're Looking For

Required:

  • 3–10 years of experience as an ML Engineer, Applied Scientist, or Research Engineer.
  • Proficiency in Python and at least one major ML framework: PyTorch, TensorFlow, or JAX.
  • Strong grasp of ML fundamentals — data preprocessing, feature engineering, model training, and optimization.
  • Hands-on experience with distributed systems, cloud ML infrastructure (AWS, GCP, or Azure), and MLOps tooling such as Weights & Biases or MLflow.
  • Comfort working with large datasets and high-throughput systems.
  • Strong bias for action, ability to work autonomously, and genuine eagerness to build something from scratch.

Compensation & Benefits

  • Salary range: $220,000 – $300,000 USD annually
  • Early-stage equity commensurate with a founding team role
  • Opportunity to define technical culture and ML infrastructure at the ground level

Location

  • On-site in Mountain View, California, United States
  • Remote work is not available for this position

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