Staff Machine Learning / Operations Research Engineer
Burq, Inc.1 day ago
Remote, United States or Remote, CanadaStaff+
Responsibilities
- Own the ML and optimization roadmap and technical direction for Dispatch OS.
- Design scalable architecture for model serving, evaluation, and optimization.
- Build and ship models for quote selection, dynamic pricing, reliability scoring, and demand forecasting.
- Develop solver-based optimization for batching, route optimization, and vehicle or fleet recommendations.
- Apply LLMs and AI agents to document extraction, quote follow-ups, and exception handling workflows.
- Build replayable evaluation frameworks and production training, deployment, monitoring, and retraining pipelines.
- Translate driver, provider, cost, and other operational constraints into model requirements and optimization formulations.
- Lead ambiguous, high-impact technical initiatives and mentor engineers through design reviews, pairing, and code review.
- Partner with Product and leadership on strategy and identify ML and operations-research opportunities.
Requirements
- 9+ years of applied ML or ML engineering experience, including multiple years at senior or staff level, with production models shipped and maintained.
- Demonstrated experience setting technical direction for ML or optimization systems whose architecture influenced a product or platform over multiple years.
- Experience leading complex cross-team technical initiatives without direct authority.
- Track record of delivering ML or optimization systems with quantified company-level business impact.
- Deep experience with decision, ranking, and scoring problems that directly drive business actions.
- Strong quantitative and algorithmic reasoning, including combinatorial problems, constraint satisfaction, and algorithm design.
- Hands-on experience formulating and solving LP, MIP, constraint-programming, or VRP-style routing problems.
- Production experience with time-series forecasting.
- Hands-on experience deploying LLM-based systems such as fine-tuned models, extraction pipelines, or agents.
- Experience owning end-to-end ML pipelines and MLOps, including training, deployment, monitoring, and retraining.
- Ability to work with messy, incomplete, constraint-heavy operational data and enforce hard business constraints.
- Experience building evaluation frameworks understandable to non-technical stakeholders.
- Preferred experience with delivery or dispatch software, TMS platforms, routing systems, commercial or open-source solvers, transportation pricing or revenue management, and published work, patents, or open-source contributions in ML, operations research, or pricing.
Benefits
- Fully remote work arrangement.
- Medical, vision, and dental insurance.
- Reimbursement for educational courses.
- Generous time off.
Categories
About Burq, Inc.
Burq builds a delivery management platform and APIs for enterprises that need reliable last‑mile logistics without stitching together multiple carriers and tools. Its Pulse AI agents automate quoting and carrier selection, dispatch across in‑house and third‑party fleets, routing, batching, exception handling, customer updates, and performance analytics for grocery, floral, and specialty retail. Founded in 2021, the company is privately held and raised a Series A in 2024.