Senior AI Engineer at compa

This role is ideal for a senior-level ML Engineer who thrives in the "0 to 1" phase of a startup. You should have at least 4 years of experience and a strong ba

Work type: onsite

Location: Orange County HQ | Denver Office | Engineering Sites- Orange County, Denver, Seattle, San Francisco

Salary: $110,000 – $220,000/yr

Type: Full-time

Summary

This role is ideal for a senior-level ML Engineer who thrives in the "0 to 1" phase of a startup. You should have at least 4 years of experience and a strong background in NLP and Large Language Models. Because this position involves building infrastructure from the ground up, they are looking for someone with "gumption" who is comfortable moving from prototype to production-grade services. The most compelling aspect of this role is the chance to build for a prestigious plate of enterprise clients like NVIDIA and OpenAI. The compensation is highly competitive ($110k - $220k), though it requires a commitment to in-person collaboration at one of their hubs in Orange County, Denver, San Francisco, or Seattle. As a member of a newly formed team, you will have significant ownership over the company’s AI technical roadmap and best practices. **You might be a good fit if you:** * Have hands-on experience deploying LLMs and classification models to solve real business problems. * Are proficient with the Python ML ecosystem (PyTorch, scikit-learn) and data pipelines. * Value in-person teamwork and want to help scale a venture-backed startup. * Can lead a project through the entire lifecycle, from data engineering to deployment.

Job Description

### About Compa

Compa is a venture-backed AI startup revolutionizing the future of compensation.

In a dynamic job market with hiring challenges, accountability, and the rise of AI, companies need the best data to stay ahead of industry changes, competition, and costs. Compa has developed the premier real-time compensation data platform, delivering top-tier compensation intelligence to leading enterprise teams.

Compa is a compensation intelligence company built to augment enterprise compensation teams in the era of AI.

Our customers include the world’s biggest companies: NVIDIA, Stripe, DoorDash, Open AI, TMobile, Moderna, Workday, Ulta, Target, and more.

Locations:

Compa headquarters are located in Irvine, California, with growing sites in Denver, Colorado and San Francisco, California. We’re a collaborative, curious, and driven team that values transparency, ownership, and continuous learning and prioritizing in person work where possible.

The Role:

As an Applied AI Engineer on Compa’s newly formed Applied AI team, you will own and lead projects across Compa’s product suite, internal operations, and be part of a team that takes a commercialized ML service from 0 to 1.

In this role you will:

• Ship ML features and services that enable the world’s best companies to make smarter pay decisions

• Lead ML-based projects from end-to-end: scoping and planning, data collection and feature engineering, model training and deployment, backend implementation, and online experimentation

• Prototype ML solutions in close collaboration with product and engineering teams, iterating rapidly based on customer feedback and business requirements

• Build Compa’s ML infrastructure from the ground up: develop models, establish deployment pipelines, and manage production systems that serve enterprise customers as well as internal operations

• Drive technical excellence and establish ML best practices across the team

• 4+ years of industry experience building and deploying ML models to solve real-world problems and deliver measurable business value

• Hands-on experience with classification, embeddings, natural language processing, and large language models

• Proficiency in Python, SQL, Git, and common ML frameworks (scikit-learn, XGBoost, PyTorch, or similar)

• Gumption — experience working at early-stage startups

• Experience with NLP techniques such as sentence transformers or semantic similarity

• Experience with model serving frameworks (FastAPI or similar)

• Familiarity with experiment tracking tools (MLflow or similar)

• Experience with data pipeline technologies (Prefect or similar)

• Experience with cloud platforms (AWS, GCP, Azure, etc.)

• Comfortable with Docker and basic CI/CD workflows

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