Founding Machine Learning Engineer

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

Benefits offered by this job

Equity participation as a foundingteam

Opportunity to establish technical方向

Job summary

Clera in Mountain View, CA is seeking a founding-level Machine Learning Engineer to help build and scale core ML systems from the ground up—bridging research and engineering to design, train, and ship production-grade models for frontier AI labs and enterprise customers.

You will own end-to-end ML pipelines, implement and fine-tune LLMs, embeddings, and generative models, and collaborate with data and product teams to translate ideas into measurable ML impact while helping shape the company’s

Qualifications

• 3–10 years of ML engineering or research experience.
• Proficiency in Python and a major ML framework (PyTorch, TensorFlow or JAX).
• Experience with distributed compute and cloud ML infra (AWS/GCP/Azure).
• Experience with MLOps tools like Weights & Biases or MLflow.

Responsibilities

• Build and optimize end-to-end ML pipelines from data ingestion to deployment.
• Implement and fine-tune LLMs, embeddings, and generative models.
• 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.

Skills

Python

PyTorch

TensorFlow

JAX

Distributed systems

MLOps

Data preprocessing

Feature engineering

Model training

Large datasets

Tools

AWS

GCP

Azure

Weights & Biases

MLflow

Job description

About the Role

This is a founding-level Machine Learning Engineer role at a well-funded Series A AI data and services startup based in Mountain View, CA. You will join a small, high-caliber team building and scaling core ML systems from the ground up — bridging research and engineering to design, train, and ship production-grade models for top AI frontier labs. This is a high-ownership position where your work directly shapes the company's technical culture, infrastructure, and long-term ML impact.

The company specializes in high-quality training and post-training data, reinforcement learning environments, and intelligent agents — serving both frontier AI labs and enterprise customers. 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 and cloud ML infrastructure (AWS, GCP, or Azure).

• Familiarity with 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 excitement about building from scratch.

Compensation & Benefits

• Base salary: $220,000 – $300,000 USD annually

• Equity participation as a founding team member

• Opportunity to establish technical direction and culture at an early-stage, high-growth company

Location

• On-site — Mountain View, California, United States

• Visa sponsorship is not available for this position