Mathematical optimisation jobs

Contribute to design and development of end-to-end AI solutions that include mathematical optimisation, modelling, and simulation approaches.
Visualise complex datasets and model outputs using the latest front-end technologies.
Work together with senior optimisation engineers and AI engineers in the team, focused on product delivery and support.
Liaise with other engineers to enhance our technological stack, to enable the adoption of the latest advances in AI and software engineering.
Contribute to various solutions and applications that may cover a broad range of business areas, sometimes at once.

Requirements

MSc or above
Nice to have: control and robotics
Nice to have: deployment of AI tools
Nice to have: interactive applications
Nice to have: full-stack apps

Skills

operations research mathematical optimisation CPLEX

Associate Principal AI Engineer - Mathematical Optimisation

AstraZeneca · Posted Nov 5, 2026

Open

Cambridge, Cambridgeshire, United Kingdom
Hybrid
Full-time · Senior

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The role involves designing, developing, and supporting end-to-end AI and optimisation solutions across complex business challenges in the pharmaceutical industry to improve efficiency and benefit patients worldwide.

Compensation

Competitive + Excellent Benefits

Responsibilities

Design, develop, and support end-to-end AI and optimisation solutions across a broad range of business challenges
Design, build, and support tools that transform how AstraZeneca operates at scale
Collaborate with a global team of AI engineers, data scientists, scientists, and software developers
Translate business challenges into well-defined engineering problems
Contribute to the deployment of interactive applications

Requirements

MSc or above
Nice to have: LLM
Nice to have: Control and robotics
Nice to have: Full-stack apps
Nice to have: Dashboarding

Skills

Operations Research AI Mathematical Optimisation Modelling Python

Associate Principal AI Engineer - Mathematical Optimisation

AstraZeneca · Posted Nov 5, 2026

Open

Cambridge, England, United Kingdom
Hybrid

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Design, develop and support end‑to‑end AI and optimisation solutions for the pharmaceutical industry.

Compensation

Competitive + Excellent Benefits

Responsibilities

Contribute to design and development of end‑to‑end AI solutions that include mathematical optimisation, modelling, and simulation approaches.
Visualise complex datasets and model outputs using the latest front‑end technologies.
Work together with senior optimisation engineers and AI engineers in the team, focused on product delivery and support.
Liaise with other engineers to enhance our technological stack, to enable the adoption of the latest advances in AI and software engineering.
Contribute to various solutions and applications that may cover a broad range of business areas, sometimes at once.

Requirements

MSc or above
Nice to have: control and robotics
Nice to have: deployment of AI tools
Nice to have: interactive applications
Nice to have: full‑stack apps

Skills

operations research mathematical optimisation CPLEX

Applied Scientist - Research Engineer (Optimisation), EMEA

Mistral · Posted Nov 4, 2026

Open

Paris

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Applied Scientists and Research Engineers focused on optimisation and operational research to post-train large language models and develop tools and frameworks for optimisation tasks.

Responsibilities

Run pre-training, post-training and deploy state of the art models on clusters with thousands of GPUs.
Generate and curate datasets for optimisation modelling (LP, MILP, constraint programming, scheduling, routing), and build evaluators and benchmarks for operational research tasks.
Use solvers as verifiers to build reward signals for reinforcement learning.
Develop the necessary tools and frameworks to facilitate data generation, model training, evaluation and deployment.
Collaborate with cross-functional teams to tackle complex use cases.

Requirements

PhD / Master in a relevant field (Operational Research, Applied Mathematics, Machine Learning)
Nice to have: ex-founder or builder
Nice to have: reinforcement learning using verifiable rewards
Nice to have: LLM-based optimisation modelling (e.g. NL4Opt-style problem formulation)
Nice to have: industry experience in supply chain, logistics, energy, or scheduling

Skills

PyTorch JAX large language models

Working Student Product Structuring & Pricing

Uniper · Posted Nov 4, 2026

Open

Düsseldorf, North Rhine-Westphalia, Germany
On-site
Internship · Intern
0+ years

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Assist in pricing and valuing renewable power products such as PPAs and BESS contracts, supporting quantitative modelling and market analysis.

Responsibilities

Support financial valuations of renewable power contracts
Enhance and calibrate quantitative models and tools
Conduct market and trend analysis on energy prices
Assist in analysing and visualising valuation results using Python, Excel, Power BI, Databricks
Work closely with senior analysts to interpret analytical results and prepare presentations

Requirements

Bachelor's degree in Mathematics, Energy Economics, Energy Engineering or related quantitative subject
Nice to have: Power market knowledge
Nice to have: Renewable energy knowledge
Nice to have: PPA and BESS contract familiarity

Skills

Python Excel Power BI Databricks NumPy SciPy pandas

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