Clera
Founding Machine Learning Engineer
About this role
Join an early-stage AI company as a Founding Machine Learning Engineer to build production ML systems serving frontier AI labs. You'll own end-to-end model development—from training LLMs and embeddings to deploying optimized inference systems—while establishing technical infrastructure and best practices alongside a small, high-ownership team.
What you'll do
- Design and optimize full ML pipelines covering data ingestion, model training, and deployment
- Implement and fine-tune LLMs, embeddings, and generative models for production use
- Build distributed training and inference systems on cloud infrastructure
- Develop model monitoring, evaluation, and continual learning frameworks
- Collaborate with data and product teams to translate requirements into measurable impact
- Establish ML best practices around versioning, reproducibility, and scalability
What they're looking for
- Python programming
- PyTorch, TensorFlow, or JAX
- ML fundamentals (data preprocessing, feature engineering, optimization)
- Distributed systems and cloud ML infrastructure (AWS, GCP, Azure)
- MLOps tooling (Weights & Biases, MLflow)
- Large-scale data handling and high-throughput systems
- Model training and inference optimization
- Autonomous problem-solving and ownership mindset
Benefits
- Competitive base salary $220,000–$300,000 USD
- Founding-level equity and impact
- On-site team environment in Mountain View
- Opportunity to shape technical culture from day one
- Work with frontier AI labs
- Autonomy and high ownership of technical decisions
Opens the application — the Jobs AI extension fills it for you. Set up autofill
Opens the official application on the employer’s site. No login required.
Clera
Clera builds an agentic operating system that automates complex workflows and processes through AI agents, with a platform designed to simplify distributed infrastructure management for developers. The company is hiring Founding Engineers, Customer Engineers, and Product Engineers to develop both backend systems and user-facing interfaces across their AI automation products.
View all jobs at CleraLikely interview questions
- Walk us through an end-to-end ML project you built—how did you handle data preprocessing, model selection, and deployment?
- Describe your experience optimizing training or inference for large-scale distributed systems. What frameworks and cloud services did you use?