Founding Engineer - Machine Learning

About the Role

A well-funded AI/ML platform startup (Series A) based in Mountain View, CA is looking for a Founding Engineer – Machine Learning to build and scale core ML systems from the ground up. You'll join a small, high-velocity team working closely with the founders to establish technical culture, reliable ML pipelines, and measurable product impact. This is a rare opportunity to shape the architecture and direction of ML infrastructure at an early stage.

What You'll Do

• 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.

What We're Looking For

Required:

• 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.

Nice to Have:

• Experience with vector databases and retrieval-augmented generation (RAG) workflows.

• Experience with continual learning, model monitoring, and evaluation frameworks.

Compensation & Benefits

• Salary: $220,000 – $300,000 USD annually

• Early-stage equity commensurate with a founding engineer role

• Note: Visa sponsorship is not available for this position

Location

Onsite in Mountain View, CA. This is not a remote role.

Originally posted on Himalayas