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    Research Engineer - London, United Kingdom - Flexciton

    Flexciton
    Flexciton London, United Kingdom

    Found in: Jooble UK O C2 - 1 week ago

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    Description

    Job Description

    About the role

    We're looking for an Optimisation Engineer who will be an exceptional addition to our small tight-knit team. As our Optimisation Engineer, you will contribute significantly to the software of our core Flexciton product.

    You will work in a technical multi-disciplinary team in a company which values collaboration and continuous learning working with large and technologically advanced factories in the most exciting industries. Some of your responsibilities will involve:

    What you'll be doing

    • Contribute to the design, implementation and support of advanced scheduling algorithms
    • Implement algorithms and reviewing code in Python considering high quality production standards.
    • Improve the performance, the quality and the scalability of our optimisation technology
    • Analyse raw data, to produce useful insights which will be used in the optimisation models or optimisation solving techniques.
    • Integrate data science models with optimisation models. To incorporate uncertainty in the optimisation (stochastic optimisation) or to deal with the uncertainty of real-life problems (e.g. robust optimisation, risk-constrained heuristics).
    • Working on live trials with direct client interaction

    Optimisation engineers at Flexciton have been involved in a broad range of activities, such as deep R&D projects, helping design our product roadmap and working closely with our customers. There is significant scope to mould the role to your interests and skills once you join the team

    What we are looking for in you

    • Experience in a SaaS company or an MSc/BSc in Operations Research, Mathematics, Industrial Engineering, Statistics, Computer Science or related field
    • Competent scripting in languages such as Python, Java, C/++
    • Experience with modelling problems using optimisation methods such as MIP / MILP
    • Strong knowledge of algorithms and data structures
    • Familiar with object-oriented programming.
    • An eye for detail and a willingness to learn about optimisation methods and or advanced scheduling algorithms
    • Able to balance mathematical rigor with a start-up mindset to ship and iterate software constantly

    Nice to have:

    • Familiar with heuristic and meta-heuristic optimisation algorithms, e.g. greedy, tabu search, simulated annealing, evolutionary algorithms or CPLEX.
    • Have successfully deployed a model in a live production environment
    • Knowledge of Git, SQL, testing + CI, Docker & Kubernete
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