Ellison Institute of Technology Oxford on cord

Ellison Institute of Technology Oxford

Research Engineer

External position
Oxford, UK
Hiring internally for Ellison Institute of Technology Oxford?
Research
Translating scientific discovery into real world impact
Posted
2 weeks ago
Checked
cord regularly checks that external positions are still open
7 hours ago

Skills & Experience

Job roles: Research Engineer
Experience level: Mid, Senior
Core skills considered: Artificial Intelligence, Machine Learning, Deep Learning, Data Pipelines, Data Modeling
Other skills considered: Data Analysis, Python, Docker, Agile, Scrum

Logistics

Base salary: Undisclosed
Some companies on cord are unable to disclose salaries publicly due to internal company policies. Message the company for salary information.
Employment type: Permanent
Remote working: Hybrid
Visa sponsorship: Not available

Job Description

As a member of the technical team focused on foundation model performance, you will play a key role in understanding, evaluating, and improving the capabilities of frontier foundation models for embodied AI and autonomous scientific experimentation. This spans both autoregressive foundation models - the sequence-modelling backbone behind language, vision-language and action prediction - and world models and world action models that learn the dynamics of the laboratory well enough to simulate, plan and act on experiments before they are run. Your research will systematically investigate how training data, model development stages, and training strategies interact to determine model capability. By uncovering these interactions, you will identify performance bottlenecks and develop novel approaches, such as new reward models, new learning curricula or data mixing strategies, that continuously improve foundation model performance.

This role offers a unique opportunity to conduct frontier research at the intersection of large-scale foundation models, data-centric AI, and embodied intelligence while solving real-world scientific problems. You will work closely with other AI researchers, software engineers, robotics engineers, and domain scientists to translate advances in autoregressive foundation models and world models into measurable improvements in autonomous laboratory performance.

The successful candidate will design and execute systematic experimental studies to understand how different data mixtures, data quality, model architectures, and training stages influence downstream capabilities and final performance in an end-to-end scientific workflow. You will identify performance bottlenecks and conduct research on improving foundation model performance through a deeper understanding of the interactions between data and models.


Responsibilities

  • Drive technical work on improving the performance of frontier foundation models - both autoregressive foundation models and world models - for autonomous scientific experimentation.
  • Conduct research into the interactions between training data and foundation models to identify the key factors limiting model performance, and develop novel data-centric approaches for continuous improvement.
  • Define and source the data needed to move model performance, working closely with domain experts across the laboratory to specify, collect, and curate high-value experimental datasets.
  • Design and maintain scalable experimentation pipelines for model training, evaluation, benchmarking, and reproducible research.
  • Analyse experimental results using rigorous scientific methodologies and translate insights into actionable improvements for model performance in a data-centric way.
  • Collaborate closely with AI researchers, software engineers, robotics engineers, and scientific domain experts to ensure research findings translate into impactful real-world scientific capabilities.
  • Contribute novel research ideas and publish high-quality research where appropriate, while maintaining a strong focus on practical deployment.
  • Communicate experimental findings and technical insights clearly across interdisciplinary teams to help shape the future direction of the AutoLab AI platform.

Requirements

  • MSc, PhD, or equivalent industry experience in Computer Science, Artificial Intelligence, Machine Learning, Robotics, or a related discipline.
  • Hands-on experience with frontier foundation models, including autoregressive foundation models such as Large Language Models (LLMs), Vision-Language Models (VLMs) and Vision-Language-Action (VLA) models, as well as embodied AI models and world models.
  • Experience with continuous pre-training, post-training, supervised fine-tuning, reinforcement learning, and other foundation model optimisation techniques.
  • Hands-on experience building end-to-end machine learning pipelines, including data curation, data mixing, model training, evaluation, performance analysis, and iterative model improvement.
  • Experience working within interdisciplinary teams.
  • Excellent written and verbal communication skills, with the ability to communicate complex experimental findings clearly across disciplines.
  • An impact-driven mindset with a passion for continuously improving model performance for real world deployment.

Desirable knowledge, skills, and experience

  • Research experience in embodied AI and robotics.
  • Research or engineering experience with world models, model-based reinforcement learning, or learned simulators.
  • Experience in working with scientific domain experts.
  • Experience with large-scale distributed training infrastructure.
  • Publications at leading AI conferences (e.g. NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, CoRL, RSS, or equivalent).
  • Experience working with large multimodal datasets, robotics datasets, or scientific datasets. Experience building scalable and reproducible experimentation and evaluation frameworks.

Personal attributes

  • Curious and analytical, with a passion for understanding why foundation models succeed or fail.
  • Strong scientific thinking combined with practical engineering skills.
  • Comfortable working in an iterative, fast-paced research environment.
  • Collaborative and proactive, with the ability to work effectively across AI, robotics, software engineering, and scientific disciplines.
  • Organised, resourceful, and capable of managing multiple experimental projects simultaneously.
  • Mission-driven, with a desire to accelerate scientific discovery through frontier AI research.

Company Benefits

  • Enhanced holiday pay
  • Pension
  • Life Assurance
  • Income Protection
  • Private Medical Insurance
  • Hospital Cash Plan
  • Therapy Services
  • Perk Box
Research Engineer at Ellison Institute of Technology Oxford
Position posted 2 weeks ago

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Starling Bank on cord

Starling Bank

Full Stack Engineer (ML Ops)

London, UK
FinTech · Banking · Finance
A better bank for everyone
Active
over 6 months ago
Responds to
0% of requests
Responds in
1h 55m
Requests
7 pending

Skills & Experience

Job roles: Full Stack
Experience level: Mid, Senior
Core skills considered: Java, React, Redux, AWS, JavaScript

Logistics

Base salary: £70K - £110K
Employment type: Permanent
Remote working: Hybrid (up to 2 remote days p/w)
Visa sponsorship: Not available

Job Description

Starling is the UK’s first and leading digital bank on a mission to fix banking! Our vision is fast technology, fair service, and honest values. All at the tap of a phone, all the time.

Starling is the UK’s first and leading digital bank on a mission to fix banking! We built a new kind of bank because we knew technology had the power to help people save, spend and manage their money in a new and transformative way.

We’re a fully licensed UK bank with the culture and spirit of a fast-moving, disruptive tech company. We’re a bank, but better: fairer, easier to use and designed to demystify money for everyone. We employ more than 3,000 people across our London, Southampton, Cardiff and Manchester offices.

Our technologists are at the very heart of Starling and enjoy working in a fast-paced environment that is all about building things, creating new stuff, and disruptive technology that keeps us on the cutting edge of fintech. We operate a flat structure to empower you to make decisions regardless of what your primary responsibilities may be, innovation and collaboration will be at the core of everything you do. Help is never far away in our open culture, you will find support in your team and from across the business, we are in this together!

The way to thrive and shine within Starling is to be a self-driven individual and be able to take full ownership of everything around you: From building things, designing, discovering, to sharing knowledge with your colleagues and making sure all processes are efficient and productive to deliver the best possible results for our customers. Our purpose is underpinned by five Starling values: Listen, Keep It Simple, Do The Right Thing, Own It, and Aim For Greatness.

Hybrid Working

We have a Hybrid approach to working here at Starling - our preference is that you're located within a commutable distance of one of our offices so that we're able to interact and collaborate in person. We don't like to mandate how much you visit the office and work from home, that's to be agreed upon between you and your manager.

Our Data Environment

Our Data teams are excited about the value of data within the business, powers our product decisions to improve things for our customers and enhance effective and agile decision making, regardless of what their primary tech stack may be. Hear from the team in our latest blogs or our case studies with Women in Tech.

We are looking for talented data professionals at all levels to join the team. We value people being engaged and caring about customers, caring about the code they write and the contribution they make to Starling. People with a broad ability to apply themselves to a multitude of problems and challenges, who can work across teams do great things here at Starling, to continue changing banking for good.

Requirements

We have built our entire banking platform in house and mostly in Java. We are looking for people who want to work on building the tooling that is used by our engineers on a daily basis.

We are looking for people who are truly full stack, and are as comfortable polishing their javascript front end as they are debugging the innards of their java applications database interactions, or standing up infrastructure with terraform. We are looking for people who can:

  • Design REST apis.
  • Code backend services, ideally using Java, or another other server side compiled language.
  • Develop modern front ends, ideally using React and Redux.
  • Get their code into the cloud and support it there, ideally on AWS.
  • Believe in clean coding, simple solutions, automated testing and continuous deployment.
  • Like to take ownership of a feature from the original idea through to live.
  • Think (like us) that a small number of empowered developers is the right way to deliver software.

Company Benefits

  • 33 days holiday (including flexible bank holidays)
  • An extra day’s holiday for your birthday
  • 16 hours paid volunteering time a year
  • Part-time and/or flexible hours available for most roles
  • Salary sacrifice, company enhanced pension scheme
  • Life insurance at 4x your salary
  • Hybrid/remote working
  • Private Medical Insurance with VitalityHealth including mental health support and cancer care. Partner benefits include discounts with Waitrose, Mr&Mrs Smith and Peloton
  • Generous family-friendly policies
  • Varied social groups set up and run by our employees
  • Perkbox membership giving access to retail discounts, a wellness platform for physical and mental health, and weekly free and boosted perks
  • Access to initiatives like Cycle to Work, Salary Sacrificed Gym partnerships and Electric Vehicle (EV) leasing

Full details are available on our careers site

Interview Process

Interviewing is a two way process and we want you to have the time and opportunity to get to know us, as much as we are getting to know you! Our interviews are conversational and we want to get the best from you, so come with questions and be curious. In general you can expect the below, following a chat with one of our Talent Team:

  • Stage 1 - 30 mins with one of the team
  • Stage 2 - Take home challenge
  • Stage 3 - 90 mins technical interview with two team members
  • Stage 3 - 45 min final with an executive and a member of the people team
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