ML Engineer — Production AI Systems, Equity Eligible

Golden Gate Recruiting; San Francisco (CA); On-site; USD 155,000 - 230,000; Full time

Job summary

Golden Gate Recruiting partners with a fast-growing AI startup backed by Browder Capital. They seek a Machine Learning Engineer to build and ship ML systems powering the core product, owning training, evaluation, and production deployment end to end.

You will design, train, and monitor models; build data and training pipelines; collaborate with product and infra to ship models into production; stay ahead of ML research and bring the best of it to the roadmap.

Qualifications

• 3+ years of experience building and deploying ML models in production.
• Strong Python skills with hands-on PyTorch or TensorFlow experience.
• Solid grasp of the full ML lifecycle: data prep, training, evaluation, deployment.
• Thrives in a fast-moving, ambiguous startup environment.

Responsibilities

• Design, train, and evaluate ML models that power core product features.
• Build and maintain data and training pipelines built for rapid experimentation.
• Partner with product and infrastructure teams to ship models straight into production.
• Monitor model performance in production and iterate fast based on real-world feedback.
• Stay ahead of ML research and bring the best of it to the roadmap.

Skills

Python programming

PyTorch

TensorFlow

ML lifecycle

Startup environment

Education

BS/MS in Computer Science or ML

Tools

Hugging Face Transformers

LangChain

LlamaIndex

Pinecone

Weaviate

Weights & Biases

MLflow

Airflow

Snowflake

BigQuery

Docker

Kubernetes

AWS SageMaker

GCP Vertex AI

Job description

Golden Gate Recruiting partners with a fast-growing AI startup backed by Browder Capital. They seek a Machine Learning Engineer to build and ship ML systems powering the core product, owning training, evaluation, and production deployment end to end.

You will design, train, and monitor models; build data and training pipelines; collaborate with product and infra to ship models into production; stay ahead of ML research and bring the best of it to the roadmap.