9 of 9 Remote Optimization Problems Jobs

. Excellent written and verbal communication skills. Experience with some programming language (Java/python/C++) Research experience in one or more: Combinatorial optimization problems (e.g., scheduling, vehicle routing, facility location). Continuous optimization problems (e.g., linear programming, convex programming, non-convex programming … a fast-paced applied research environment. Ability to handle ambiguity. Top tier publications pertinent to the field of study. KEY JOB RESPONSIBILITIES Solve complex optimization and machine learning problems using scalable algorithmic techniques. Design and develop efficient research prototypes that address real-world problems in … world problems, in real-world speed, while failing & learning along the way. We use modular algorithmic designs in the domain of combinatorial optimization, solving complicated generalizations of core OR problems with the right level of decomposition, employing parallelization and approximation algorithms. We use deep learning More ❯

scientists to develop scalable ML models and deploy them into production environments using modern MLOps practices. If you're excited about solving real-world optimization problems, building high-performance ML infrastructure, and working with autonomous agent simulations, this is your opportunity to make a significant impact. This … enhance simulation tooling and infrastructure to enable faster-than-real-time modelling of 1,000+ autonomous agents for various use cases such as fleet optimization, logistics, or robotics. Develop, deploy, and maintain machine learning models, with a strong focus on reinforcement learning (RL) and multi-agent systems to optimize … containerization and orchestration using Docker and Kubernetes. Hands-on experience with reinforcement learning frameworks such as OpenAI Gym or Stable-Baselines3. Practical knowledge of optimization algorithms and probabilistic modeling techniques (e.g., Bayesian methods, Gaussian Belief Propagation). Experience integrating models into real-time decision-making systems or multi-agent More ❯

scientists to develop scalable ML models and deploy them into production environments using modern MLOps practices. If you're excited about solving real-world optimization problems, building high-performance ML infrastructure, and working with autonomous agent simulations, this is your opportunity to make a significant impact. This … enhance simulation tooling and infrastructure to enable faster-than-real-time modelling of 1,000+ autonomous agents for various use cases such as fleet optimization, logistics, or robotics. Develop, deploy, and maintain machine learning models, with a strong focus on reinforcement learning (RL) and multi-agent systems to optimize … containerization and orchestration using Docker and Kubernetes. Hands-on experience with reinforcement learning frameworks such as OpenAI Gym or Stable-Baselines3. Practical knowledge of optimization algorithms and probabilistic modeling techniques (e.g., Bayesian methods, Gaussian Belief Propagation). Experience integrating models into real-time decision-making systems or multi-agent More ❯

door instantly. Duties: Design and refine models that accurately predict customer demand, providing critical insights that guide operations across the business. Tackle large-scale optimization problems to ensure stock is distributed efficiently, keeping stores and warehouses perfectly balanced. Take ownership from concept to launch—designing, building, deploying More ❯

door instantly. Duties: Design and refine models that accurately predict customer demand, providing critical insights that guide operations across the business. Tackle large-scale optimization problems to ensure stock is distributed efficiently, keeping stores and warehouses perfectly balanced. Take ownership from concept to launch—designing, building, deploying More ❯

from proposed improvements Collaborate with engineers and operations leads to embed models into planning and execution Translate operational and commercial constraints into tractable optimisation problems Work with MLEs and Staff Data Scientists to productionise models and build scalable optimisation pipelines Bring a scientific lens to operational design; measure … to non-technical audiences Comfortable working across functions and disciplines to drive impact Nice to haves Experience working on routing, scheduling, or network optimisation problems Experience in fast-scaling startups or operational teams Experience in logistics, mobility, marketplaces, or other operationally complex businesses What we offer 25 days More ❯

that drive the ToffeeX engineering design software. You will collaborate with a multidisciplinary team to solve complex engineering problems, focusing on mathematical optimization, numerical methods for partial differential equations (PDEs), and computational geometry. This role offers the opportunity to work at the intersection of advanced mathematics, engineering … Responsibilities: Develop and refine mathematical models and algorithms to address complex engineering challenges, particularly those involved in multi-physics simulation and associated PDE-constrained optimization problems. Collaborate with engineers and software developers to integrate new features and improvements into our cloud-based platform, bringing value to customers. Contribute to … numerical methods for PDEs, mathematical modelling or PDE-constrained optimization. Hands-on experience in developing and implementing numerical algorithms for solving complex simulation or optimization problems. You thrive in a fast-paced, collaborative environment Desirable Skills & Experience: Research level experience developing FVM/FEM solvers for physical systems. Experience More ❯

service, we have a long history of creating magical moments for our customers! We're not about selling products - we want to solve problems and change lives through Monzo ️ The Customer Operations team provides tech-led and human support experiences for now over 10 million customers. We don … t just solve customer problems - we aim to improve customer satisfaction and product engagement by providing effortless, fast, and empathetic support. Our Operations tech team has three focus areas: Creating in-app experiences that enable customers to solve their own problems . As well as building … further the organisation's goals and strategy, bringing the right level of clarity, urgency and rigour as appropriate. Work on solving multi-faceted optimisation problems at scale, such as how to maximise the leverage of technologies like LLMs to aid human workers or how to forecast, schedule and More ❯

and rigour as appropriate. Oscillate between contributing to high-level planning and strategy and organisational leadership and diving deep into the execution of problems and getting hands-on as necessary. Use your expert knowledge and experience to lead architectural discussions for complex systems in the collective. You'll … make decisions. You have a track record of balancing speed of execution with technical excellence, delivering resilient systems for consumer products. You solve problems end-to-end, from client applications to backend infrastructure. You have technically led across 3-4 teams to solve complex optimisation problems. You're More ❯