Research Delivery Manager (AI/Optimisation Projects) We are looking for a Research Delivery Manager to lead the delivery of an AI-powered optimisation project focused on building a next-generation auto-scheduling solution.
This is a unique role at the intersection of delivery management, research, data-driven decision-making, and optimisation. You will work closely with optimisation engineers and technical experts, helping transform an open-ended research challenge into structured, measurable progress.
This is not a traditional Project Manager or Delivery Manager role. You will not manage feature delivery or software development timelines. Instead, you will help a research team stay focused on the right experiments, evaluate results based on evidence, and ensure the project reaches its key milestones. What you will do * Own the delivery of a 12-week optimisation Proof of Concept (POC), ensuring progress towards key milestones and decision points. * Transform a research plan into a structured experiment portfolio with clear goals, dependencies, and success criteria. * Track experiments, test cases, results, and learnings to maintain a clear view of project progress. * Help the team evaluate experiments based on data and evidence rather than assumptions. * Facilitate discussions between optimisation engineers, technical stakeholders, and business teams to drive decisions. * Identify risks, blockers, and dependencies early and coordinate solutions. * Keep research engineers focused on the most valuable problems and prevent unnecessary work. * Prepare clear delivery updates, reports, and insights for stakeholders. * Improve processes and remove friction from the research workflow. * Use modern AI tools to support reporting, documentation, analysis, and team efficiency.
What we are looking for * Experience delivering complex technical, research, AI, ML, data, or optimisation projects. * Strong analytical mindset and ability to evaluate results based on data. * Experience working with experiments, hypotheses, testing, and evidence-based decision-making. * Ability to work with technical teams and understand research-oriented environments. * Strong communication and stakeholder management skills. * Ability to bring structure to ambiguous problems and open-ended projects. * Experience managing risks, dependencies, and project progress. * Experience with tools such as Jira, Linear, Confluence, Notion, or similar.
Backgrounds that could be a great fit We are open to different profiles, including: * Delivery Managers with a strong analytical or QA/testing background. * Technical Project Managers or Product Owners working with AI, ML, or data products. * ML Engineers or Data Scientists who moved into delivery/project leadership. * Researchers or technical leads experienced in managing complex experiments and teams.
What matters most You don’t need to be an optimisation expert or write algorithms yourself.
The key is your ability to: * keep research teams focused on the right questions; * understand whether an experiment provides meaningful evidence; * turn uncertainty into structured progress; * communicate clearly with both technical and business stakeholders.
Nice to have * Experience with AI/ML projects. * Experience working with optimisation, algorithms, simulations, or mathematical modelling. * Experience in research-driven environments. * Scientific or engineering background.
Why join? You will work on a challenging AI optimisation project where your contribution will directly influence how technology solves complex real-world scheduling problems.
You will collaborate with experienced optimisation engineers and be part of building a solution where experimentation, data, and innovation are at the core.
