Staff Machine Learning, Operations Research Engineer

🔥 0 minutes ago

🌐 United States, Canada – Remote

🇺🇸 United States – Remote 🇨🇦 Canada – Remote

⏰ Full Time

🔴 Lead

📚 Research Engineer

👻 Ghost score 20%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Burq

WebsiteLinkedInAll Job Openings

11 - 50 employees

🍽️ Food & Beverage

🏥 Healthcare

🏗️ Construction

💰 Pre Seed Round on 2021-06

Food & Beverage • Healthcare • Construction

Burq is a comprehensive delivery platform that enables businesses across various industries, including e-commerce, food, floral, health & wellness, and construction, to offer on-demand delivery services. By integrating with Burq, companies can connect seamlessly with multiple delivery providers, allowing them to scale quickly to new markets and improve customer satisfaction with same-day and efficient delivery options. Burq also provides advanced tracking technology and does not charge commissions, ensuring optimal delivery solutions for businesses. With a focus on easy integration and a broad network of delivery providers, Burq empowers businesses to offer reliable delivery services without the need to build their own infrastructure.

📋 Description

• Define and build the intelligence at the core of Dispatch OS, Burq's platform for ML-assisted dispatch decisions • Set technical direction for how Burq prices, selects, forecasts, and routes deliveries • Personally build high-leverage models and optimization systems • Own the ML and optimization roadmap and make key technical bets • Design end-to-end architecture for model serving, evaluation, and optimization at scale • Lead ambiguous, high-stakes modeling and optimization problems from framing through production • Guide technical work across Engineering and Data • Set standards for experimentation, evaluation, and production ML • Mentor engineers through design reviews, pairing, and code review • Partner with Product and leadership on product strategy and ML/OR competitive advantage • Design and ship quote-selection, dynamic-pricing, and reliability-scoring models • Build demand and volume forecasting models • Develop solver-based optimization for batching, route optimization, and vehicle/fleet recommendation • Apply LLMs and AI agents to dispatch workflows, including provider-rule extraction and quote follow-ups • Build replayable evaluation frameworks for customer model validation • Translate operational constraints into model requirements, scoring logic, and optimization formulations • Design and own automated MLOps pipelines for training, deployment, monitoring, and retraining • Use AI tools daily to accelerate experimentation, evaluation, and debugging

🎯 Requirements

• 9+ years in applied ML or ML engineering, including multiple years operating at the senior or staff level, with models shipped to and maintained in production • Track record of setting technical direction for ML or optimization systems, where architecture decisions you made shaped a product or platform over multiple years • Demonstrated ability to lead complex technical initiatives across teams without direct authority • Track record of ML or optimization systems with quantified, company-level business impact (e.g., tens of millions in revenue, or major utilization or margin gains), ideally in pricing, logistics, marketplaces, or operations • Deep experience with decision, ranking, and scoring problems where model outputs directly drive a business action • Strong quantitative and algorithmic reasoning, including combinatorial problems, constraint satisfaction, and algorithm design • Hands-on experience formulating and solving optimization problems (LP/MIP, constraint programming, or VRP-style routing) • Experience with time-series forecasting in production • Hands-on experience deploying LLM-based systems in production, such as fine-tuned models, extraction pipelines, or agents • Experience owning end-to-end ML pipelines and MLOps (training, deployment, monitoring, retraining) • Comfortable with messy, incomplete, constraint-heavy operational data, and able to build models that honor hard business constraints rather than treating them as soft penalties • Experience building evaluation frameworks that non-technical stakeholders can understand and trust • Nice to have: Experience with delivery/dispatch software, TMS platforms, or routing systems • Nice to have: Production experience with commercial or open-source solvers (OR-Tools, Gurobi, CPLEX) • Nice to have: Pricing or revenue management experience in aviation, fleet, or transportation • Nice to have: Published work, patents, or open-source contributions in ML, OR, or pricing

🏖️ Benefits

• Fully remote • Medical, vision, and dental insurance • Reimbursement for educational courses • Generous time off