Senior Machine Learning Scientist

Aioi Nissay Dowa Europe; Oxford; On-site; GBP 90,000 - 130,000; Full time

Benefits offered by this job

28 days annual leave

Private Medical Insurance

Life Assurance 4x

Wellbeing benefits

Wagestream financial flexibility

Season-ticket loans

Cycle scheme

Driving lessons allowance

Job summary

Aioi Nissay Dowa Europe is seeking an experienced ML researcher to advance privacy-preserving generative AI within a multi-partner lab. You will design, test and validate ML approaches such as differential privacy, federated learning and secure inference, aiming to produce reliable, deployable components.

The role involves mentoring junior researchers, coordinating with internal teams and external partners, and disseminating results through publications and talks.

Qualifications

• Master's or PhD in Computer Science or related field or equivalent research/industry experience.
• 5+ years of relevant work experience.
• Strong track record in applied ML/AI research or development.
• Deep understanding of modern ML methods and their limitations.
• Strong software engineering foundations in Python, ML frameworks, version control, CI/CD, and reproducible experiments.

Responsibilities

• Lead or contribute to technical research workstreams within CODAS tracks and ensure timely high-quality outputs.
• Design, develop and validate ML models for privacy-preserving generative AI including differential privacy and federated learning.
• Serve as a technical research lead on assigned workstreams and adapt methods to meet programme objectives.
• Translate research outcomes into proof-of-concept systems and deployable components.
• Mentor junior ML engineers and research associates; discuss scoping and tasks.
• Contribute to publications, technical reports and conference presentations.

Skills

ML research

Python

CI/CD

Reproducible experiments

Mentoring

Communication

ML lifecycle

Privacy-preserving ML

Federated learning

Education

Master's or PhD in CS/ML

Tools

Python

ML frameworks

Version control

CI/CD pipelines

Job description

The role will support the development of a privacy-preserving generative AI ecosystem designed to protect personal and sensitive corporate data by design, including data residency, anonymisation and secure deployment protocols and principles, as well as model-based data protection achieved during both training and inference time. Working within a multidisciplinary and multi-partner environment, the postholder will research technical concepts core to the program and contribute towards developing them into dependable systems and components that can be used in live settings, while also supporting the broader technical development of the Lab and its collaboration with CODAS and other project partners. Additionally, the postholder will create publishable material based on the work carried out in the program, and attend events such as conferences and workshops to disseminate the progress made.

Responsibilities

• Lead or substantially contribute to technical research workstreams within assigned CODAS tracks, setting experimental direction and ensuring delivery of high-quality outputs within programme timelines.
• Design, develop and validate machine learning models, algorithms and approaches for privacy-preserving generative AI, including areas such as differential privacy, federated learning, and secure inference.
• Serve as a technical research lead on assigned workstreams; design novel approaches or adapt existing methods to meet programme objectives beyond the current state of the art.
• Contribute to the translation of research outcomes into proof-of-concept systems, toolkits and deployable components that form part of the programme deliverables.
• Work with internal colleagues and external project partners to understand technical requirements, constraints and delivery priorities.
• Mentor and support junior colleagues (ML engineers and research associates), scoping and delegating tasks aligned to their development and the needs of the programme.
• Contribute to scientific publications, technical reports, conference presentations and other dissemination activities in support of the programme’s commitment to advancing the field.
• Champion best practices in ML research, software design, experimental rigour, reproducibility and responsible AI across the team.
• Communicate complex technical findings and trade‑offs clearly to both technical and non-technical stakeholders, including partner organisations and programme leadership.

Essential Qualifications

• A Master’s degree or PhD in Computer Science, Machine Learning, Statistics, Mathematics, or a closely related discipline, or equivalent research or industry experience.
• 5+ year work experience in relevant field.
• A strong and demonstrable track record in applied ML/AI research or development, with recognised expertise in one or more relevant areas such as privacy-preserving ML, generative AI, large language models, or federated learning.
• Deep understanding of modern ML methods, their assumptions and limitations, and the ability to reason about appropriate application in novel or constrained settings.
• Strong software engineering foundations in Python, including ML frameworks, version control, CI/CD, and reproducible experimental practices.
• Strong skills handling challenging data that requires understanding, preparation, organisations and augmentation before use for the purposes of ML/AI research or development.
• Experience working across the full ML lifecycle — from problem framing, experimentation and prototyping through to evaluation, integration and deployment.
• Ability to contribute to scientific publications, technical reports, and the dissemination of research findings to a wide audience.
• Proven ability to mentor or support junior colleagues and scope technical work aligned to team and programme goals.
• Strong communication skills, with the ability to explain complex technical concepts and trade‑offs clearly to both technical and non-technical audiences.
• Ability to work effectively in technically complex and ambiguous environments involving multiple stakeholders.

Desirable Qualifications

• Experience with privacy-preserving ML techniques such as differential privacy, federated learning, secure computation, or membership inference resistance.
• Experience with generative AI systems, large language models, agentic AI approaches, or evaluation methodologies for frontier AI.
• Familiarity with cloud platforms (AWS, GCP, Azure) and MLOps tooling.
• Contributions to open-source AI or ML projects, or a track record of published research in relevant areas.
• Experience working in a multi-partner programme involving industry, government or academia.
• Experience in consulting, client-facing AI delivery, or regulated industry contexts such as insurance, financial services, or public-sector programmes.
• Familiarity with agentic systems design, MCP/A2A protocols, or inference-time privacy controls.
• Familiarity with innovating with agentic-driven workflows and toolsets for research and prototyping tasks, such as Claude, Claude-Code, CoPilot, etc.

Benefits

• 28 days annual leave with the option to buy/sell up to 5 days holiday.
• Private Medical & Permanent Health Insurance.
• 4× Annual salary Life Assurance.
• Health and wellbeing benefits including money back on health-related expenses (optician, dental, physio, etc.), flu jab vouchers, virtual GP service, employee assistance programme, and enhanced family‑friendly policies (baby bonus & pension advisory service).
• Financial and lifestyle support such as financial flexibility through Wagestream, annual season ticket loans, cycle scheme, and £250 towards driving lessons for you and dependents.
• Subject to company performance and completion of probation.

Aioi Nissay Dowa Europe is committed to promoting equal opportunities in employment. Employees and job applicants will receive equal treatment regardless of age, disability, gender reassignment, marital or civil partner status, pregnancy or maternity, race, colour, nationality, ethnic or national origin, religion or belief, sex or sexual orientation (Protected Characteristics).

At AND‑E, equal opportunity is more than a policy—it’s a promise. We welcome applications from all individuals regardless of age, disability, gender identity, marital status, pregnancy, race, religion, sexual orientation, or any other protected characteristic.

Reasonable adjustments: If you require any adjustments to support you during our recruitment process, please let us know. We’re committed to making the process accessible and are happy to help.