Labeling Analyst

Shape the Future of Autonomous Driving

We are partnering with an innovative autonomous vehicle company to find a Labeling Analyst who’s passionate about quality, precision, and cutting-edge technology. This role plays a critical part in delivering high-quality labeled data used to train and evaluate machine learning models that power real-time, safety-critical autonomous driving systems.

If you have a sharp eye for detail, enjoy problem-solving, and like working at the intersection of operations and technology, this is an exciting opportunity to make a real impact.

What You’ll Do

As a Labeling Analyst, you’ll work closely with internal teams and third-party partners to ensure labeling accuracy and continuous quality improvement. Your responsibilities will include:

• Reviewing data labels using internal and third-party tools to identify defects, mislabels, or missing labels
• Documenting findings, updating issue trackers, and writing clear, concise reports
• Filing bugs and submitting feature requests with detailed documentation
• Collaborating cross-functionally with technical, operational, and infrastructure teams
• Helping define tool requirements, executing testing, and creating user-facing documentation
• Supporting additional tasks such as QA analytics, log selection for labeling, and workflow coordination

What We’re Looking For

• Strong attention to detail and comfort working as an individual contributor
• Experience using Google Workspace (Docs, Sheets, etc.)
• Clear written and verbal communication skills
• Technical aptitude with the ability to collaborate across teams
• QA experience is a plus—but not required

Why This Role?

• Work on cutting-edge autonomous vehicle technology
• Be part of a growing team supporting business expansion and innovation
• Gain hands-on experience with real-world machine learning and data QA processes
• Competitive hourly pay with full-time stability on a long-term contract

Work Schedule & Location

• 40 hours per week
• Hybrid role: onsite 2–3 days per week
• Candidates must be based in or near Pittsburgh, PA

Interview Process

• Technical screening (experience, skills, and fit)
• 3 technical interview rounds (including a 45-minute Zoom session)
• Onsite, in-person hands-on assessment
• 2 non-technical interview rounds