Founding Machine Learning Engineer
About the Role
A Series A AI/ML startup focused on model training and evaluation is looking for a Founding ML Engineer to build and scale core machine learning systems from the ground up. This is a hands-on, high-impact role for someone who thrives at the intersection of research intuition and engineering execution. You will work closely with the founding team to design, train, and ship production-grade ML models while helping set the foundation for technical culture, infrastructure, and research practices.
What You'll Do
-
Build and optimize end-to-end ML pipelines, from data ingestion 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
-
3–10 years of hands-on experience as an ML Engineer, Applied Scientist, or Research Engineer.
-
Proficiency in Python and at least one of PyTorch, TensorFlow, or JAX .
-
Experience building production-grade end-to-end ML pipelines (data ingestion, training, deployment).
-
Experience implementing and fine-tuning LLMs, embeddings, and generative models for real-world applications.
-
Hands-on experience with distributed training/inference and scalable ML systems.
-
Experience with cloud platforms ( AWS, GCP, or Azure ) and ML tooling ( MLflow, Weights & Biases ) for experimentation and model tracking.
-
Strong collaboration skills; ability to work cross-functionally with data and product teams.
-
Bias for action, autonomy, and eagerness to shape something from scratch.
Location
This role is on-site in Mountain View, California . Authorization to work in the US without visa sponsorship is required.
Compensation
$220,000 – $300,000 USD annually , commensurate with experience.
Originally posted on Himalayas