VP of Optimization
Pelico
About Pelico
We are creating the factory of the future where disruptions are avoided, processes synchronized and value captured. Our factory operations management platform enables factory teams to be more agile and resilient in a world where supply chain disruptions occur every 16 minutes. Pelico empowers users to identify bottlenecks, avoid problems, and focus on innovation instead of fire-fighting. Since our foundation in 2019, we’ve partnered with industry leaders across aerospace, industrial equipment, and luxury watchmaking, revolutionizing factory operations in over 15 countries. Esteemed clients include Airbus, Safran, Cartier, Daikin, and Eaton.
Our Team
With a dynamic team of over 180 professionals across the US and France, Pelico is a melting pot of top-tier talent from Tech, Data Science, and Manufacturing domains.
Our collaborative environment fosters innovation and excellence, driving us to solve complex challenges and shape the future of manufacturing.
Our work has been recognized by Safran (Digital Transformation Award) and Microsoft (scale-up of the year).
Engineering turns Product ambition into scalable, reliable solutions that empower on-site operational teams .
We design a platform that handles high volumes, concurrent users, and complex workflows , while remaining modular, maintainable, and future-proof.
The mission
Manufacturers run on systems of record — ERP, MES. Pelico sits on top and turns that raw data into a live, realistic model of the plant: a supply-chain twin that projects what will actually be produced and shipped, and where it will fall short. And it already goes further than flagging the risk: Pelico prescribes actions and lets planners act on them, writing decisions back to the systems of record. Pelico is already both a system of information and a system of action .
The next frontier is to take that much further. In a real factory, exceptions and disruptions never stop — a late part, a quality hold, a slipped operation — and the plan drifts from execution within hours. We want every decision-maker — human planners and , increasingly, AI agents — resolving those disruptions continuously (expediting or chasing a supplier, pulling in / pushing out orders, re-allocating scarce stock, re-sequencing work orders, sourcing an alternative), and all of them pulling in the same direction: the next best action prescribed for each, and every one of them unified against a single objective.
That direction is a single, configurable North Star (OTD, turnaround, inventory €, revenue). The twin is both the world every action plays out in and the judge that scores it — pricing any action's global impact so local decisions converge to the company objective instead of fighting each other. It's a hard, open problem: multi-objective, continuous and reactive, bounded by real feasibility, trustable and explainable, and increasingly multi-agent — agents in conflict, order-dependent outcomes, arbitration. Expect the full toolbox: exact solvers where they fit, neighborhood search and metaheuristics where they don't, and reinforcement-learning-style formulations where the twin is the environment and the North Star is the reward.
What you'll own
Own the optimization strategy. Define the vision and multi-quarter roadmap for optimization at Pelico — what to build in-house versus buy, what to sequence when, which bets to make — and tie every one of them to the company's objectives. You're accountable to leadership for the outcomes, and you set the technical direction the whole discipline follows. As one of the company's senior technical voices, you have a seat at the table — helping shape product and company strategy, not only your own function.
Build and lead the team. Found, hire, and grow a credible optimization team from the ground up: develop careers, set the technical and cultural bar, and own its performance and delivery. You are the draw that pulls top OR talent toward a company not yet known for it. Partner with product and engineering leadership to embed optimization across the roadmap.
Represent Pelico's OR to the world. Thought leadership is part of the job: publish, speak, and represent Pelico in the field to build our research and employer brand. Forge partnerships with universities and research labs that feed both the science and the hiring funnel.
Back the commercial front. Be an asset in strategic deals, where trust is earned, not assumed. Lend pre-sales credibility, win over skeptical customers, and build the senior technical relationships that turn optimization into revenue.
The core optimization. A sample of the problem space, not an exhaustive list: allocation and recommendations beyond FIFO (multi-objective, under real constraints); the North Star scoring and conflict-arbitration layer that aligns humans and agents; optimization under uncertainty (lead/cycle times and yield as distributions, not point estimates); and stock/safety-policy optimization — computed from our own historical actuals, not declared ERP parameters.
Trust and adoption. An optimizer only creates value when a planner acts on it. You'll own the optimality-vs-runtime trade-off deliberately, keep every recommendation explainable, and validate it against how plants really behave — because here, explainable and trusted is a hard constraint, not a nice-to-have.
Agent-actionable optimization. Expose the twin and its scoreboard as clean, governed, explainable tools an AI agent can call to read the plan, simulate an action, score it, and act under human-in-the-loop gates.
Lead by example. Author the models and specs, write and review code, and mentor strong engineers into optimization technique. At this level, the leadership and the engineering are the same job.
What you bring
A PhD in Operations Research, Applied Mathematics, or a related field, and a senior track record solving real optimization problems in industry.
Recognized thought leadership — a body of work (publications, patents, talks, open-source) and the authority that comes from having cracked genuinely hard problems.
Deep production experience across combinatorial optimization (MILP/LP/CP), metaheuristics, and simulation — equally comfortable reaching for an off-the-shelf solver (Gurobi / CPLEX / OR-Tools / Hexaly) and hand-crafting a bespoke algorithm when no solver fits or is fast enough, at scale (millions to hundreds of millions of records).
The judgment to make the exact-vs-heuristic, optimality-vs-speed trade-off deliberately — and the drive to build a team and a discipline, not just models.
At home in an AI-native environment — comfortable packaging optimization as tools that AI agents can consume.
Still hands-on in the code: the strongest in the room, not the one who left the keyboard.
Bonus: supply-chain / manufacturing planning depth (MRP, multi-level BOM, pegging, scheduling); optimization packaged for agent consumption.
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