Clera

Founding Engineer- Machine Learning

Remote Founding ML Engineer role with clear candidate location fit.

PostedJul 11, 2026

Eligible countries1 accepted country

Seniority signalLead

Work settingRemote

Accepted candidate locations

USA

Role overview

Readable role content extracted into sections for faster review.

Build and optimize end-to-end ML pipelines from data ingestion through deployment.
Implement and fine-tune LLMs, embeddings, and generative models for real-world use cases.
Develop efficient training and inference systems leveraging distributed compute.
Partner with data and product teams to translate ideas into measurable ML outcomes.
Contribute to model monitoring, evaluation, and continual learning frameworks.
Establish best practices for model versioning, reproducibility, and scalability.
Move quickly between experimentation and production deployments, balancing research and engineering rigor.

3–10 years of experience as an ML Engineer, Applied Scientist, or Research Engineer.
Strong ML fundamentals: data preprocessing, feature engineering, model training, and optimization.
Proficiency in Python and at least one deep learning framework: PyTorch, TensorFlow, or JAX.
Experience with distributed training/inference and cloud ML infrastructure (AWS, GCP, or Azure).
Hands-on experience building end-to-end ML pipelines from data ingestion to production deployment.
Familiarity with MLOps tooling (e.g., Weights & Biases, MLflow) and model monitoring approaches.
Comfortable working with large datasets and high-throughput systems.
Bias for action, ability to work autonomously, and eagerness to build systems from scratch.
Willingness to work onsite in Mountain View, CA.

Experience with vector databases and retrieval-augmented generation (RAG) workflows.
Experience with continual learning, model monitoring, and evaluation frameworks.