Principal Operations Research Scientist

About Quvia:

Quvia is building the digital fabric between edge and cloud. Our platform uses AI and machine learning to orchestrate connectivity across satellite terrestrial and hybrid networks so customers can move and manage data in the worlds most network constrained environments.

We partner with global leaders in aviation maritime energy and other industries where connectivity is variable and complex and digital services depend on reliable data movement. As companies deploy AI automation and data-driven systems at the edge Quvia provides the platform needed to unlock the full potential of their data and build value above the network.

Quvia is a fast growing Series A company backed by Colombia Capital ($5B in fund commitments. It is headquartered in the greater Miami are with offices in the UK and India.

Learn more atand Quvia

• Founded in 2019 we are a fast-growing Series A tech startup passionate about making connectivity experiences better for everyone.
• Our industry-first solutions are already addressing major challenges for companies in the travel and transportation industries-and were just getting started.
• As an early-stage company new hires will have the opportunity to make a significant impact on our growth trajectory.
• We are headquartered in the greater Miami region with remote teams spanning the U.S. Europe and India.
• Quvia is backed by Columbia Capital a respected venture capital firm founded in 1989 that has raised over $5 Bn of fund commitments.

About the Role

Quvia is deploying Grid our AI-powered platform that dynamically routes network traffic to optimize connectivity and performance with enterprise customers in the U.S. Were looking for the engineer or scientist who makes it perform.

The core problem is getting finite satellite bandwidth to the right users at the right time under contested and fast-changing conditions. Capacity shifts as satellites move demand is bursty and mission-driven and the answer has to be both good and fast. If youve built scheduling network flow or supply-chain optimization systems at scale you already know the math. The domain is the only new part.

Youll be embedded with enterprise customer as the senior technical owner of Grids optimization layer. This is hands-on work not advisory. Youll formulate the models write the code choose the solvers and profile the results yourself. Youll also translate in both directions: turning mission constraints into problems Grid can solve and explaining what the models can and cant do in terms program leads can act on.

Eligibility: U.S. citizenship required for this position

What Youll Do

• Formulate and build optimization models:Take the customers operational problems bandwidth allocation routing scheduling capacity planning contention resolution and turn them into rigorous mathematical formulations then implement them in production code.
• Develop and extend Grids optimization capability:Modify and configure Grid directly against the engagements requirements and write new solvers heuristics and decomposition schemes where the existing capability doesnt reach.
• Own solver and algorithm selection: Decide where exact methods (MILP network flow constraint programming) are the right tool and where the problem demands heuristics metaheuristics decomposition or a hybrid and be able to defend the choice.
• Tune for hard runtime constraints: Live deployments impose real time budgets. Profile reformulate tighten relaxations warm-start and cut where needed to get quality solutions inside the window.
• Validate rigorously: Build the test harnesses benchmark instances and solution-quality measures that show a model is behaving correctly including against edge cases the customer will eventually hit.
• Instrument and diagnose live systems: Debug degraded solution quality infeasibility and performance regressions in deployed environments where you cannot simply re-run offline.
• Document formulations assumptions and model behavior to a standard that holds up under government program review.
• Feed the roadmap: Bring field learnings back to Quvias OR and engineering teams and identify where new optimization capability is needed in the product.
• Support the full engagement lifecycle: initial configuration pilots evaluation and steady-state operation.
  

What Youll Need

• U.S. Citizenship - Non-negotiable for this customer engagement.
• 8 years of professional experience developing and deploying optimization or operations research systems in production. Seniority and judgment are an explicit part of the bar; this is not a role we will fill with a strong junior.
• Advanced degree (MS or PhD) in Operations Research or a closely related quantitative field. Computer Science and Electrical Engineering backgrounds are equally welcome where the optimization depth is there. Equivalent industry experience will be
  considered in place of the degree.
• Deep applied command of optimization techniques: linear and mixed-integer programming network flow constraint programming column generation or other decomposition methods metaheuristics and large-scale scheduling with the practical experience to know which to reach for and when.
• Strong software engineering ability. You will write and ship the models yourself. Production-quality code in a compiled or high-performance language (Java C or similar) alongside Python for modeling and analysis.
• Hands-on experience with commercial and open-source solvers Gurobi CPLEX OR-Tools HiGHS or similar including modeling APIs parameter tuning and callbacks.
• Track record of working directly with external customers or stakeholders on complex technical engagements with the communication skills to hold a technical conversation and a program conversation on the same day.
  

Preferred Qualifications

• AI/ML experience particularly where learned components sit alongside or inside optimization systems: demand forecasting feeding an allocation model learned heuristics or branching rules or reinforcement learning for sequential decisions.
• Background in supply-chain logistics or delivery network optimization the kind of work done at Amazon DoorDash Walmart Labs or comparable operations at scale.
• Queueing theory and congestion modeling characterizing contention latency and service levels when demand exceeds available capacity.
• Discrete-event and Monte Carlo simulation and simulation-optimization where an analytical model alone wont capture the systems behavior.
• Stochastic robust and multi-stage optimization recourse models scenario generation chance constraints and designing for uncertainty rather than around it.
• Dynamic programming Markov decision processes and approximate DP for sequential allocation and control problems.
• Multi-objective optimization and trade-off analysis including how to present a Pareto frontier to a decision-maker who has to choose a point on it.
• Graph and network algorithms shortest path max-flow/min-cut matching and network design at scale. Forecasting time-series and statistical modeling feeding operational models plus design of experiments and sensitivity analysis to test how far a solution holds.
• Algebraic modeling languages Pyomo JuMP AMPL or GAMS for rapid formulation and prototyping.
• High-performance and parallel computing applied to optimization: distributed solves parallel heuristics and profiling large model runs.
  

Work Conditions

• U.S.-based with regular travel to and on-site work at customer locations.
• Some coordination with UK-based colleagues and stakeholders; occasional early or late calls to cover the time difference.
  

What Well Offer

• Connectivity and content engineering and business knowledge
• Opportunity to work in cross-functional teams
• Competitive Salary
• 401(k) with 100% match up to 4.0% after one year of service
• Competitive health benefits including optical and dental
• Life Insurance
• Performance Bonus
• Flexible paid time off policy
• Monthly Phone Allowance

Quvia will never ask to interview job applicants via text message or ask for personal banking information as part of the interview process. Quvia will never ask job applicants or new hires to send money or deposit checks for the case of doubt please contact us directly at

Quvia Inc. is an Equal Opportunity Employer. Employment opportunities at Quvia Inc. are based upon ones qualifications and capabilities to perform the essential functions of a particular job. All employment opportunities are provided without regard to race religion sex (including sexual orientation and transgender status) pregnancy childbirth or related medical conditions national origin age veteran status disability genetic information or any other characteristic protected by law.

Required Experience:

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