Staff ML Engineer — Scale a World-Class Marketplace

Angi; Denver (CO); On-site; USD 230,000 - 310,000; Full time

Benefits offered by this job

Year-end performance bonus

Equity package

Medical, dental, vision

Flexible vacation

Pet discount plans

401K with company match

Job summary

Angi is seeking a Staff Machine Learning Engineer to lead ML initiatives for homeowner-pro search ranking and recommendations. You will deploy models at scale, design robust MLOps, and collaborate with platform teams to deliver low-latency services in a marketplace setting.

The role emphasizes end-to-end ML capabilities, from data pipelines to CI/CD, with mentorship and a long-term technical vision. Experience with LLMs and distributed systems is highly valued.

Qualifications

• 6+ years in data science and machine learning, ideally in tech marketplaces.
• Hands-on experience post-training and self-hosting open-weight LLMs.
• Strong knowledge of evaluation metrics and end-to-end MLOps lifecycle.

Responsibilities

• Lead development of ML/AI models for marketplace ranking, recommendations and matching.
• Design robust MLOps for deployment, monitoring, CI/CD and model registries.
• Define rigorous offline and online evaluation if ML systems to ensure quality.
• Collaborate with engineers, data scientists and product managers across teams.
• Contribute to long-term technical vision and roadmap with leadership.
• Mentor junior engineers and foster knowledge sharing.

Skills

SQL

Python

TensorFlow

PyTorch

MLOps

Model deployment

Distributed systems

Communication

Education

Master’s or PhD in a quantitative field

Tools

vLLM

SGLang

Job description

Angi is seeking a Staff Machine Learning Engineer to lead ML initiatives for homeowner-pro search ranking and recommendations. You will deploy models at scale, design robust MLOps, and collaborate with platform teams to deliver low-latency services in a marketplace setting.

The role emphasizes end-to-end ML capabilities, from data pipelines to CI/CD, with mentorship and a long-term technical vision. Experience with LLMs and distributed systems is highly valued.