Machine Learning Engineer

Zof AI; San Francisco (CA); On-site; USD 140,000 - 210,000; Full time

Benefits offered by this job

MacBook Pro

Premium AI tools

Cursor Ultra

Claude Code Ultra

OpenAI Codex Max or equivalent

High-performance AI environment

Job summary

Zof AI in San Francisco is seeking a Machine Learning Engineer to own the full model lifecycle—training, evaluating, fine-tuning, and deploying models for production. You will build and maintain data pipelines, datasets, and labeling processes, ensuring rigorous evaluation and robust model quality within our products.

The role emphasizes hands-on development, strong ML fundamentals, and a pragmatic approach to when to train versus API calls, with collaboration across AI and product engineering

Qualifications

• Hands-on experience training and fine-tuning models.
• Strong grounding in ML fundamentals and evaluation methodology.
• Experience with Python and the modern ML stack.
• Experience building datasets and data pipelines.
• Strong software engineering discipline.
• Clear written and verbal communication.
• Comfort operating in a fast-moving environment.
• Evidence of models shipped to production or rigorous applied work.

Responsibilities

• Train, fine‑tune, and evaluate models for production use.
• Build and maintain datasets, labeling pipelines, and data quality checks.
• Own training infrastructure and experiment tracking.
• Develop applied models that power verification and quality features.
• Establish rigorous evaluation and regression testing for models.
• Decide when to train, when to fine‑tune, and when to call an API.
• Collaborate with AI and product engineers to ship models into features.
• Own the model lifecycle from data through production monitoring.

Skills

Python

ML fundamentals

Data pipelines

Software engineering

Model deployment

Communication

Fast-paced

Production models

Tools

PyTorch

JAX

TensorFlow

Job description

Machine Learning Engineer

San Francisco, CA – Full-time, Mid to Senior, On-site

Compensation

• Competitive salary
• Plus meaningful equity

About This Role

Zof AI is seeking a Machine Learning Engineer for the traditional ML discipline: training, fine-tuning, and evaluating models rather than only building on top of them. This role owns datasets, training pipelines, and the applied models that power verification and quality systems inside our products. The ideal candidate is rigorous about evaluation, comfortable owning the full model lifecycle, and pragmatic about when a trained model beats an API call.

Responsibilities

• Train, fine‑tune, and evaluate models for production use.
• Build and maintain datasets, labeling pipelines, and data quality checks.
• Own training infrastructure and experiment tracking.
• Develop applied models that power verification and quality features.
• Establish rigorous evaluation and regression testing for models.
• Decide when to train, when to fine‑tune, and when to call an API.
• Collaborate with AI and product engineers to ship models into features.
• Own the model lifecycle from data through production monitoring.

Requirements

• Hands‑on experience training and fine‑tuning models.
• Strong grounding in ML fundamentals and evaluation methodology.
• Experience with Python and the modern ML stack.
• Experience building datasets and data pipelines.
• Strong software engineering discipline.
• Clear written and verbal communication.
• Comfort operating in a fast‑moving environment.
• Evidence of models shipped to production or rigorous applied work.

Nice to have

• Experience fine‑tuning LLMs or working with embeddings at scale.
• Experience with PyTorch, JAX, or similar frameworks.
• Experience with model serving and inference optimization.
• Published work, competition results, or strong open‑source contributions.

What we provide in San Francisco

• MacBook Pro
• Premium AI development tools
• Cursor Ultra
• Claude Code Ultra
• OpenAI Codex Max or equivalent advanced AI tooling
• Access to a high‑performance AI product environment
• Close collaboration with leadership, engineering, and customers
• Opportunity to work in the San Francisco AI ecosystem
• Wellness and productivity support where applicable
• Competitive startup environment
• High ownership
• Direct product impact

Benefits may depend on role and final offer terms.