Machine Learning Engineer

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 is thrilled to be partnering with a fast-growing AI startup backed by Browder Capital — one of the earliest investors in breakout companies like Wander.com and Owner.com. This team is putting AI to work solving real problems for real customers, and momentum is building fast across engineering, go-to-market, and design.

THE ROLE

Our client is looking for a Machine Learning Engineer ready to build and ship the ML systems that power their core product — with real ownership spanning training and evaluation all the way through production deployment.

TECH STACK & TOOLS

• Python — building with PyTorch or TensorFlow
• Hugging Face Transformers for cutting-edge NLP/LLM work
• LangChain or LlamaIndex to orchestrate LLMs and power RAG pipelines
• Vector databases like Pinecone or Weaviate driving fast retrieval
• Weights & Biases or MLflow to track experiments and version models
• Airflow driving data pipelines, with Snowflake or BigQuery as the data warehouse
• Docker and Kubernetes for deployment, running on AWS SageMaker or GCP Vertex AI

WHAT YOU'LL DO

• 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

WHAT WE'RE LOOKING FOR

• 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
• BS/MS in Computer Science, Machine Learning, or a related field (or equivalent experience)

NICE TO HAVE

• Experience with LLMs, fine-tuning, or retrieval-augmented generation
• Experience with distributed training or large-scale data pipelines

COMPENSATION

$155,000–$230,000 base salary + meaningful equity. Target pay generally maps to years of directly relevant experience: 3–4 years $155,000–$175,000; 5–7 years $175,000–$200,000; 8+ years $200,000–$230,000. Bands reflect 2026 early-stage startup market data (seed/Series A–B) for this role and location; final offers may vary based on the candidate's specific background.