[Remote] AI Optimization Engineer

Note: The job is a remote job and is open to candidates in USA. Datacor is the leading provider of software solutions to the process manufacturing space, and they are seeking an AI Optimization Engineer to lead and define optimization capabilities across their product suite. This role involves setting technical direction, establishing algorithmic foundations, and driving delivery from design through production deployment, while collaborating with cross-functional teams to ensure solutions meet real user needs.

Responsibilities

• Define and lead the technical strategy for optimization use cases across Datacor's product portfolio
• Translate complex, real-world operational constraints into rigorous mathematical models
• Design, implement, and benchmark optimization algorithms including exact methods, metaheuristics (simulated annealing, tabu search, genetic algorithms), and commercial solvers (OR-Tools, Gurobi, CPLEX, or equivalent)
• Make principled tradeoffs between solution quality, computational cost, and real-time responsiveness
• Collaborate closely with product, engineering, and design teams to ensure the solver doesn't just work algorithmically it becomes a solution that real users can understand, trust, and act on every day
• Drive end-to-end delivery of optimization solutions from prototype to production working across cross-functional teams
• Integrate optimization engines into production software via APIs and enterprise data pipelines
• Serve as the internal authority on optimization methods communicating algorithm design, performance, and tradeoffs clearly to both technical and business audiences
• Stay ahead of advances in OR, combinatorial optimization, and applied AI and bring new ideas and thinking that push our capabilities forward

Skills

• Master's degree in Operations Research, Industrial Engineering, Computer Science, Applied Mathematics, or a related quantitative field with 3+ years of hands-on industry experience, or a PhD in a related field
• Proven track record of taking optimization solutions from problem definition to production with measurable business impact across domains such as supply chain, logistics, production scheduling, vehicle routing, or related fields
• Proficiency with at least one major OR/optimization framework: Google OR-Tools, Gurobi, CPLEX, HiGHS, SCIP, or equivalent
• Strong programming skills in Python; C++ or Java a plus
• Hands-on experience with cloud platforms, particularly AWS, including deploying and scaling computational workloads
• Familiarity with Large Language Models (LLMs) and generative AI, and an awareness of how they can complement optimization workflows
• Exceptional communication skills able to translate complex algorithmic concepts into clear, business-relevant terms for non-technical stakeholders, and convey the value of your work in a way that resonates across the organization
• Ability to model ambiguous, real-world constraints rigorously and defend and advocate for design decisions at all levels of the organization
• Genuinely curious you ask why the problem exists, not just how to solve it, and you bring that curiosity into every stage of the work
• Strong product ownership mindset you take responsibility for outcomes, not just outputs, and care about whether your solution actually works for the people using it
• Outcomes-driven you measure success by the real-world impact your work delivers, not by the sophistication of the technology or elegance of the process behind it. The goal is results that matter to the business and the customer
• Impactful experience in one or more of the following: transportation, logistics, supply chain, fleet management, manufacturing or mill production scheduling, or the agri-food industry
• Familiarity with geospatial data and road network routing APIs (e.g., Google Maps Platform, HERE, Mapbox)
• Experience leading optimization work within an Agile, cross-functional product team
• Comfort integrating optimization outputs into enterprise software workflows and ERP data models

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