Sr. Applied Machine Learning Engineer

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

Plug is an automotive fintech startup building the marketplace for electric vehicles. Consumers, dealers and commercial partners trade in, sell and auction used EVs on a platform built only for electric vehicles. Nothing in it is adapted from legacy automotive.

Consumers get an instant cash offer in minutes, backed by data-driven pricing and battery state-of-health analysis. Pickup, payment and title transfer are handled end to end. Franchise and independent dealers across the United States bid in real time on inventory sourced directly from these consumers, dealers and commercial partners. Sellers get a fast, fair exit, and dealers get a dedicated channel for sourcing used EV inventory.

Plug was founded in 2023 and is led by former Tesla executives. It is backed by a $20M Series A from Lightspeed Venture Partners. We're building the most AI-native startup team in Los Angeles: operators, engineers and ML researchers building the transaction rails for the fast-growing used EV market.

• You'll help build the biggest infrastructure opportunity in automotive.

• You'll work on a platform built only for EVs, with nothing adapted from legacy automotive.

• You'll be part of an AI-native company that is rethinking how work gets done.

• You'll work directly with operators who have scaled multi-billion-dollar businesses in automotive, EV and marketplaces.

• You'll work alongside a small, senior team, with high autonomy and a direct line to company outcomes.

Every 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.

• Build and ship agents and multi-agent workflows for operations, dealers, and sellers: document extraction, inspection and title review, dealer and seller communication, and internal tooling.

• Trace every agent so you can see each step, tool call, and decision. Use those traces to debug failures and turn them into new eval cases.

• Write evals before and alongside each agent: build datasets from real cases, measure accuracy and failure modes, and gate changes to prompts, models, and tools on the results.

• Make model and prompt decisions with data: compare options on accuracy, cost, and latency, and run upgrades when a model is deprecated or a cheaper one holds up.

• Integrate agents with the services the team already owns, through clean APIs and tools. Work within the existing architecture and raise design concerns with the owning engineer instead of routing around them.

• Ship full-stack when the job calls for it: the TypeScript and React screens where people review and correct agent output, and the backend endpoints behind them.

• Help the rest of engineering adopt the same patterns. Build reusable tools, examples, and short write-ups that make the next agent faster to build.

• 5+ years of full-time industry software engineering, with a track record of shipping features to production and supporting them after launch.

• Hands-on experience shipping LLM features to production: tool use, retrieval, and structured output.

• Experience building evals and tracing for LLM systems: datasets drawn from real cases, automated scoring, and production traces you used to find and fix failures. We care less about which agent framework you used (e.g., Claude Agent SDK, LangChain Deep Agents) than how you knew it worked.

• Strong TypeScript or Python, and comfort working across the stack: APIs, databases, and frontend when needed.

• You work agent-first. You’ve built your own tooling around coding agents, such as skills, MCP servers, custom workflows, or evals.

• You enjoy being part of a small team: pairing, reviewing each other’s work, sharing credit, and building inside systems other people designed. You can disagree, make your case, and then ship the agreed plan.

• A habit of writing things down: short design notes, eval results, and runbooks that others can pick up.

• High agency in an ambiguous, fast-moving startup. You find the most valuable workflow to automate and ship against it without waiting for a perfect spec.

• BS in computer science, math, statistics, or a related quantitative field, or equivalent experience.

Annual 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.

• 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.
Acknowledgments

Plug is an equal opportunity employer. We don’t discriminate based on race, color, religion, creed, national origin, ancestry, sex, gender, gender identity or expression, sexual orientation, pregnancy, age, marital status, military or veteran status, physical or mental disability, medical condition, genetic information, or any other characteristic protected by law. Plug will consider qualified applicants with arrest and conviction records in accordance with the Los Angeles Fair Chance Initiative for Hiring and the California Fair Chance Act.