Develop and improve a new software product that manages customer orders across a multi-sensor constellation of satellites.
Locations (3)
Toulouse, Occitanie, France
San Francisco, California, United States
Golden, Colorado, United States
Responsibilities
Develop and improve a new software product that manages customer orders across a multi-sensor constellation of satellites
Interface with teams to help design the customer-facing interfaces and the back-end pipeline that goes from a plan to onboard execution
Build tools and services that help sales and operators understand current and future capacity, operational risks and opportunities for growth
Solve complex multi-objective optimization problems that maximize collection capacity, balancing various customer constraints
Design systems of systems: decompose complex problems into well-bounded services with clear interfaces, and reason about how they interact, fail, and scale together
The Applications Scientist will provide technical on-site support to enlarge POR share, develop and maintain positive relationship with customers and will bridge new product penetration, support pre-sales efforts with technical presentations, BKM and white papers.
Compensation
Onto Innovation Inc. offers competitive salaries and a generous benefits package
Responsibilities
Initiates the design, development, execution and implementation of scientific research projects.
Investigates the feasibility of applying scientific principles and concepts to potential inventions and products.
Plans and executes laboratory research.
Maintains substantial knowledge of state-of-the-art principles and theories, and may contribute to scientific literature and conferences.
Participates in development of patent applications.
Requirements
Fresh B.S./M.S. in Engineering Sciences, Materials Science, Electrical Engineering, Chemical Engineering, Applied Sciences
Provide analytical decision‑support for Universal Destinations & Experiences leadership, influencing data‑driven operational and workforce decisions using industrial engineering, operations research, and advanced analytics.
Responsibilities
Design, operationalize, and sustain end‑to‑end analytical and decision-support solutions using industrial engineering and business analytics principles.
Apply structured analytical techniques—including probability and statistics, process flow analysis, queuing theory, mathematical optimization, scenario modeling, and prescriptive optimization solvers to diagnose problems.
Develop and maintain decision-support models for labor planning, workforce utilization, budgeting, scheduling, and hiring strategies.
Partner closely with operational leaders to define problems, frame decisions, and drive adoption of data-driven solutions.
Acquire and prepare data using database querying tools and modern data pipelines.
Requirements
Bachelor’s degree in Industrial Engineering
Operations Research
Management Science
Decision Science
Nice to have: Master’s degree in Industrial Engineering, Operations Research, Management Science, or Decision Science
The role involves building and extending large-scale simulations of global traffic placement, solving capacity planning as constrained optimization, building production forecasting for peak demand, and leading technical direction across multiple teams.
Responsibilities
Build and extend large-scale simulation of global traffic placement: how traffic shifts across edge sites as demand grows and as sites, peering links and backbone paths fail.
Work with the load-balancing team on simulation fidelity and performance, and validate results against production behavior and live failure tests
Formulate and solve capacity planning as constrained optimization: where to add compute, peering and caches, given space, power, supply, latency and failure constraints.
Build and tune the solvers
Plan capacity for the browsers, proxies and caches Meta's services and AI agents use to reach the internet, and find which one becomes the bottleneck as Meta's internet access needs grow.
Pay range (monthly salary): zł/gross 10 150 - 18 850
Responsibilities
Responsibility for maintaining and developing maintenance system in order to assure safety, improve machine reliability, reduce costs and optimize spare parts inventory
Manages personal budget against actual spend
Leads projects in the field of TPM (especially autonomous maintenance, RCA, skills matrix, 5S), spare parts optimization and machinery technical improvement
Initiate and lead the projects in terms of savings, optimizations and recapex
Manages and guides the professional development of the team
Requirements
University degree in engineering / technical sciences
Build and maintain AI/ML systems for logistics optimization at Allegro.
Compensation
PLN 14 600 - 20 825
Annual bonus based on your annual performance and company results.
Responsibilities
Data Modeling & Analysis
Operations Research & Optimization
AI System Development & Innovation
Data Processing & Automation
Data Management & Pipeline Reliability
Requirements
Graduated with a degree strongly related to quantitative methods or statistical & mathematical modeling, such as Data Science, Mathematics, Physics, Econometrics, Computer Science, Engineering, Logistics, or a similar major.
Nice to have: Airflow
Nice to have: Google Cloud Composer
Nice to have: Gemini Enterprise Agent Platform (Vertex AI)
Postdoctoral researcher applying data science, machine learning, optimization, and reliability methods to energy systems.
Compensation
The pay for this position is $105,144.00 Annually.
Responsibilities
Apply data science, machine learning, optimization, and reliability and risk analysis methods to hydropower, marine energy, and other power system assets
Contribute to software and data tools that support decision making by the energy industry and research sponsors
Conduct reliability analysis and risk assessment of marine energy technologies and prepare journal publications
Develop machine learning-based prediction of dynamic loading on energy infrastructure under icing conditions
Create an electricity price database and integrate price forecasting into optimization-based valuation tools
Requirements
PhD in electrical engineering, power and energy systems, industrial/systems engineering, mechanical engineering, data science, operations research, computer science, or other relevant disciplines
The role involves supporting data analytics projects, analyzing business processes, cleansing data, and developing prototypes to optimize road network decisions.
Responsibilities
Support the execution of data analytics projects in collaboration with the supervisor/project lead.
Involvement in the analysis of the business processes as well as the derivation of problem areas and analytical requirements.
Identification and collection of required data as well as data cleansing.
Develop and implement prototypes for the business users.
Support the anchoring of data-driven decisions in operating business through the building up of specialist methodical knowledge and knowledge transfer from successfully completed projects.
Operations Research Engineers function as internal consultants to support improved decision-making by developing models using operations research methods, such as mathematical optimization and stochastic simulation.
Responsibilities
Participate in the scoping of business problems to apply operations research methods
Work with key contacts to identify and translate data requirements which represent the system and constraints to be modeled
Develop custom mathematical optimization and/or stochastic simulation models by applying: linear programming, mixed-integer programming, system dynamics simulation, and/or discrete event simulation
Proactively drive cross-functional alignment across organizations to validate model solution quality
Create documentation to explain how the operations research methods are applied, and conduct reviews with senior technical professionals to ensure technical quality
Help shape the next generation of auto lending by owning strategic, hands-on research that improves credit decisions, loan offers and portfolio performance—and mentoring researchers across the department.
Responsibilities
Advance credit models: Build and deploy predictive models using credit bureau, alternative and vehicle data.
Optimize loan offers: Balance pricing, terms, down payments, conversion and portfolio risk.
Improve underwriting: Evaluate data providers and develop models for fraud detection, income verification and reduced manual review.
Accelerate research with AI: Develop research agents for data exploration, experimentation and model diagnostics.
Lead research into production: Mentor data scientists, guide technical reviews and measure model impact after deployment.
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