Job Title: Sr. Applied Machine Learning Engineer
Team: Engineering
Location: Onsite - Sawtelle (Between Santa Monica & West LA)
Employment Type: Full-time, Salary, Exempt
Reports To: Head of Engineering
THE OPPORTUNITYEvery car on Plug starts with a number: what is this EV worth today, and what will a dealer pay for it tomorrow? Those numbers come from our models. They draw on auction results, market data, vehicle telematics and battery health. As volume grows, our models have to get more accurate, update faster, and be easier to trust and explain.
You'll join our Intelligence team and work alongside our ML engineer and data team, who built the models behind pricing and battery health. Together you'll take those models further: sharper price and volume forecasts, battery state-of-health models built from telematics, and LLM pipelines that pull structured data out of vehicle, title and inspection documents.
WHAT YOU'LL DO- Work with the team to build, improve and run in production the models behind instant offers, auction pricing and sell-through: valuation, price and volume forecasting, and demand signals.
- Develop battery state-of-health and vehicle-condition models from telematics and other time-series data, which is often noisy, sparse or only partly labeled.
- Take models through the full lifecycle together with the team: feature pipelines on our Snowflake/dbt stack, training, evaluation, deployment, monitoring, drift detection and retraining.
- Evaluate models by statistical accuracy and by business outcomes such as offer acceptance, margin and arbitration rate, and help build the feedback loops that connect the two.
- Bring in LLMs where they work better than traditional models, for example pulling structured data out of vehicle, title and inspection documents. Build the evaluations that show whether they hold up.
- Strengthen how the team works as it grows: experiment tracking, model registry, reproducible training and code review for ML work. Share what you know, pair on hard problems, and learn from the people who know our data best.
WHAT YOU'LL BRING- 5+ years building and shipping machine learning systems, with several models running in production that you supported well after launch, not just trained.
- Strong Python, plus deep experience with at least one modern ML framework (PyTorch, scikit-learn, XGBoost/LightGBM or similar).
- Practical experience with forecasting, regression or pricing problems on tabular and time-series data.
- Solid grounding in statistics and experiment design: validation strategy, leakage, calibration, and knowing when a metric is lying to you.
- Comfort with real-world, messy data and strong SQL. Experience with a modern data stack (Snowflake, dbt or similar) is a plus.
- Hands-on experience building with LLMs: tool use, retrieval, structured output, and above all evaluation.
- You work agent-first. You've built your own tooling around coding agents, such as skills, MCP servers, custom workflows or evals.
- A habit of writing things down: design docs, model cards and runbooks that others can pick up.
- You enjoy being part of a small team: pairing, reviewing each other's work and sharing credit.
- Comfort building inside systems other people designed. You can disagree, make your case and then ship the agreed plan.
- High agency in an ambiguous, fast-moving startup. You find the most valuable problem and ship against it without waiting for a perfect spec.
- BS or MS in a quantitative field (computer science, statistics, engineering, physics, applied math) or equivalent experience.
Nice to have- Experience with vehicle, marketplace, auction, lending or insurance pricing data.
- Experience with sensor or telematics data, battery modeling or other physical-systems data.
- Experience with transfer learning, multi-task learning or model distillation.
- Experience with ML or LLM serving on a budget for latency and cost.
COMPENSATION AND BENEFITSAnnual salary: $164,000 - $200,000
Salary ranges come from independent, third-party benchmarking against national compensation data. Where an offer falls within the range depends on relevant experience, specialized skills, training and qualifications, current business needs and market conditions. We review ranges periodically and may adjust them as the market changes.
Benefits and perks- Health, vision and dental insurance
- 401(k) plan
- 30 days of work from anywhere per calendar year
- Daily lunch stipend
- Equity (based on role and performance)
- Unlimited PTO
- Fully stocked kitchen
- Dog-friendly office
- Ongoing opportunities for growth and development
This is a full-time, in-person role based in our Los Angeles office in Sawtelle (between Santa Monica and West Los Angeles). We provide relocation assistance for candidates who need to move. Sponsorship is not available at this time.
