Sr. Applied Machine Learning Engineer (EV)

Location: Onsite in Sawtelle, Los Angeles, United States; full-time, in-person office role

Annual salary: $164,000–$200,000

Company

hirify.global is an automotive fintech startup building an electric-vehicle marketplace for consumers, dealers, and commercial partners, including data-driven pricing, battery health analysis, auctions, payment, and title transfer.

What you will do

• Build, improve, and operate production models for instant offers, auction pricing, valuation, forecasting, sell-through, and demand signals.
• Develop battery state-of-health and vehicle-condition models from telematics and noisy, sparse, partially labeled time-series data.
• Own the ML lifecycle with the team, including Snowflake/dbt feature pipelines, training, evaluation, deployment, monitoring, drift detection, and retraining.
• Evaluate models through statistical accuracy and business outcomes such as offer acceptance, margin, and arbitration rate.
• Build LLM pipelines that extract structured data from vehicle, title, and inspection documents, together with robust evaluations.
• Improve experiment tracking, model registry, reproducible training, code review, documentation, pairing, and collaboration.

Requirements

• 5+ years building and shipping machine learning systems, with multiple production models supported after launch.
• Strong Python and deep experience with at least one modern ML framework, including PyTorch, scikit-learn, XGBoost, LightGBM, or similar.
• Practical experience with forecasting, regression, or pricing problems using tabular and time-series data.
• Strong foundations in statistics and experiment design, including validation strategy, leakage, calibration, and metric assessment.
• Comfort with messy real-world data and strong SQL.
• Hands-on LLM experience with tool use, retrieval, structured output, and evaluation.
• Experience building personal tooling around coding agents, such as skills, MCP servers, custom workflows, or evaluations.
• Ability to write design documents, model cards, and runbooks; collaborate through pairing, code review, and knowledge sharing.
• High agency in an ambiguous, fast-moving startup and ability to work within existing systems, challenge proposals constructively, and ship agreed plans.
• BS or MS in computer science, statistics, engineering, physics, applied mathematics, or a quantitative 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 serving ML or LLM systems with latency and cost constraints.
• Experience with Snowflake, dbt, or a similar modern data stack.

Culture & Benefits

• Small, senior team with high autonomy and direct connection to company outcomes.
• Health, vision, and dental insurance, plus a 401(k) plan.
• 30 days of work from anywhere per calendar year, while the role itself remains onsite.
• Daily lunch stipend, equity based on role and performance, unlimited PTO, and a stocked kitchen.
• Dog-friendly office and ongoing growth and development opportunities.
• Relocation assistance is provided; visa sponsorship is not available.