166 Nlp Research Scientist jobs in the United Kingdom

About Arondite

Arondite is building the next generation of autonomous systems, software and AI to solve the world's most important frontier problems across defence, critical industries and the humanitarian sector. We are looking for mission-driven engineers who want to be part of a highly motivated team and build things that make a positive difference.

The Role

Arondite is looking for talented and flexible AI engineers to work on machine learning models for a range of autonomous systems, operating in the air, on the land and under the sea.

You will be developing models using open-source tools such as OpenCV and PyTorch for inclusion within fully integrated hardware/software products. You will be building algorithms to aid in areas such as navigation, image processing, sensor data processing and sensor fusion.

As a member of a company building integrated products, you will be able to influence the design and implementation of the data collection mechanisms, leading to more efficient models and faster training. You will also work closely with end users to rapidly understand and improve real-world model performance.

As an early hire within a start-up, you will have the opportunity to set up and drive AI development within the company. You will potentially lead the function and build a broader team as we continue to expand and build more diverse products. Regardless of previous experience, you will review the output of other engineers to check their work and provide feedback - everyone’s input is valued.

Requirements

You should apply if you have:

• BSc/BEng or MSc/MEng in AI, Computer Science, Data Science, Engineering or a related technical subject
• Strong programming skills in Python, as well as C++, Java or Rust
• Practical experience in developing machine learning models for sensor data processing
• Keen interest in applying cutting-edge machine learning approaches to real-world problems
• Interest in optimising data collection to improve machine learning performance
• Good understanding of resource optimisation of AI models to run on discrete / edge platforms

Note: The above describes the perfect candidate. We encourage you to apply even if you only partially fulfil this list.

Nice to have:

• Knowledge of MLOps in enabling machine learning to be deployed and maintained in end-user products
• Image and data processing for noise reduction / filtering
• Experience in visual representation of complex sensor data

All engineers at Arondite are expected to:

• Communicate effectively within a multi-disciplinary team of hardware, software and AI engineers
• Be resourceful and open-minded in seeking solutions to engineering challenges
• Teach themselves to be the expert, if we don’t already have one in a particular area

Please note: This is an in-person position based in London. The successful candidate must by the start of their employment have permission to work in the UK.

Benefits

We offer:

• The opportunity to work with world-class engineers on a wide range of technologies
• Free training and education to quickly fill knowledge gaps
• The best resources and equipment required to do your job
• Exposure to working closely with customers on real problems
• Free meals and snacks in the office
• 7% employer pension contribution
• Employee Stock Options for everyone, so we all have a stake in the company’s growth
• Relocation support

About EIT Oxford

The Ellison Institute of Technology (EIT) works to develop and deploy advanced technology in pursuit of solving some of humanity’s most challenging and enduring problems. Guided by world-leading scientists and entrepreneurs, EIT seeks to accelerate innovation by driving scientific and technological advancements across four humane endeavours:health and medical science, food security and sustainable agriculture, climate change and clean energy, and government innovation and the era of artificial intelligence.

Please visit eit.org for more details.

Our Culture

At the Ellison Institute, we believe that an inclusive, collaborative team atmosphere is just as important to our mission as our scientific aims and methods.

We strive to build a supportive environment where everyone feels confident taking creative risks toward innovation. We value emotional intelligence and communicating with empathy and respect for others.

We foster a team that is curious, has a deep sense of commitment, responsibility, and the resilience needed to achieve excellence.

About the AI & Robotics Team

We are a team of AI researchers, Applied AI scientists, data and software engineers within EIT. We work across all the humane endeavours, supported by world-class data platforms and large-scale compute.

AI is at the heart of how EIT tackles humanity's most pressing and enduring challenges. Our mission is to harness state-of-the-art statistical machine learning to 10x the impact of EIT’s programmes and discover novel AI approaches that lead to 100x impact in the future.

Requirements

Job Summary:

You’ll play a foundational role in building a highly collaborative, well-structured, and efficient research environment across our AI capability. Partnering closely with our Research Lead and Research Program Manager, you will enable the smooth running of research efforts connecting the research team with the rest of EIT and external partners, defining and running enabling research processes, and helping shape a strong research culture. 
 

You’ll work as part of the broader AI Operations function; driving operational excellence in close alignment and collaboration with other Operations team members.  You’ll contribute across multiple domains including partnership with Oxford University on high impact projects and play a key role in increasing effectiveness of internal events, processes, and knowledge-sharing.  You’ll thrive in a dynamic environment, bring clarity where needed, and be a consistent source of momentum behind the scenes. 

Key Responsibilities:

Research Environment and Collaboration:

• You will co-design and implement systems that foster a productive, collaborative research culture. 

• Build operating rhythms and co-ordination structures for the research team  

• Connecting with other teams across EIT to build relevant infrastructure/processes (e.g. journal access, publication processes and required infrastructure) 

• Ensure a smooth integration between AI-research and AI-wide operations 

Academic & Research Community Interaction:  

• Coordinate with Oxford University and other academic partners, especially on project logistics, people engagement, and reporting (e.g. Centre for Doctoral Training logistics) 

• Serve as the operational lead for academic partnership tracking and engagement 

• Develop and own our conference attendance approach and footprint

Internal Research Community Building: 

• Organise and manage journal clubs, tech talks, and internal seminars to drive knowledge sharing 

• Support integration between Research and Applied teams through regular syncs, shared documentation, and experiment tracking tools 

• Help set a team-wide approach to conference participation: submission support, knowledge capture, and external representation 

Project Management & Operations: 

• Own the delivery of cross-functional initiatives that support research workflows, tooling, and documentation standards 

• Track and report on progress across key research initiatives, supporting leadership in strategic decision-making 

• Champion operational excellence and efficiency through documentation, process improvement, and lightweight governance 

Essential Knowledge, Skills and Experience:

• AI Research/Tech Operations: Experience working in AI research, academic ML, or other technical environment; comfortable bridging rigor and executive
• Project Coordination: Able to drive multiple projects at once, keeping stakeholders aligned and timelines on track 
• Stakeholder Management: Skilled communicator, confident working with researchers, engineers, external partners, and internal leadership 
• Culture & Community Building: Proven ability to build environments of trust, curiosity, and open knowledge sharing 
• Operational Excellence: Detail-oriented with a strong bias to action; able to bring clarity and simplicity to evolving processes 

Benefits

Why work for EIT: 

At the Ellison Institute, we believe a collaborative, inclusive team is key to our success. We are building a supportive environment where creative risks are encouraged, and everyone feels heard. Valuing emotional intelligence, empathy, respect, and resilience, we encourage people to be curious and to have a shared commitment to excellence. Join us and make an impact! 

We offer the following salary and benefits: 

• Enhanced holiday pay  

• Pension  

• Life Assurance 

• Income Protection 

• Private Medical Insurance  

• Hospital Cash Plan 

• Therapy Services 

• Perk Box 

WHJS1_UKTJ

Role: Machine Learning Operations Engineer
Location: Oxfordshire
Salary: 65,000 - 75,000

This is an exciting opportunity to join a world leading company specialising in motion capture and tracking systems, with products used globally in the entertainment, engineering, and life sciences sectors. My Client are looking for a talented Machine Learning Operations Engineer to support and enhance their cutting edge machine learning capabilities.

The Role

You will join a collaborative Research and Development team based in Oxford, contributing to the development and maintenance of a modern ML operations stack. This includes data acquisition pipelines, data management, and machine learning model training infrastructure. The environment includes both self-managed on premise systems and cloud-based infrastructure, primarily using AWS.

You will have the opportunity to influence the technical direction of the ML Ops team, propose new areas for development, and potentially lead your own projects.

This is a hybrid role combining remote and on site working. There is no expectation to be available outside core business hours.

Key Responsibilities

• Maintain and improve ML Ops infrastructure
• Manage on premise Kubernetes clusters and ML pipelines
• Integrate ML toolkits into operational workflows
• Collaborate with ML developers to streamline workflows
• Suggest and implement technical improvements and new tools

Required Skills and Experience

• Academic background (research Masters level) or industry experience in a relevant field
• Strong experience managing on premise Kubernetes clusters
• Deep knowledge of Kubeflow or similar systems such as MLflow
• Proficient in Python and experienced with Linux systems
• Familiar with AWS services such as Cognito, S3, EC2 and Lambda
• Experience working with ML frameworks such as PyTorch or Lightning
• Capable of designing and delivering ML Ops solutions across various platforms

Desirable Skills

• Background in DevOps with experience in CI systems such as Jenkins
• Familiarity with infrastructure as code tools such as Ansible
• Interest in human motion capture, sports tech, or animation
• Exposure to C++ is a bonus

Benefits

• 65,000 - 75,000 (DOE)
• 10 percent company pension
• 25 days annual leave plus bank holidays
• Life assurance
• Private medical insurance including dental and optical
• Permanent health insurance
• Cycle to work scheme
• Free on site parking

WR Engineering are the #1 recruitment partner for engineering, manufacturing & technical sales jobs. We recruit for permanent and contract jobs UK wide.

WR is acting as an Employment Agency in relation to this vacancy.

Job Description:

We are seeking an experienced Machine Learning Engineer with expertise in big programmes and has contributed to the delivery of complex business cloud solutions. The ideal candidate will have a strong background in Machine Learning engineering and an expert in operationalising models in the Databricks MLFlow environment (chosen MLOps Platform).

Responsibilities:

• Collaborate with Data Scientists and operationalize the model with auditing enabled, ensure the run can be reproduced if needed.
li>Implement Databricks best practices in building and maintaining economic modelling (Machine Learning) pipelines.
• Ensure the models are modular. Ensure the model is source-controlled with agreed release numbering.
• Extract any hard-coded elements and parameterise them so that the model execution can be controlled through input parameters.
• Ensure the model input parameters are version-controlled and logged to the model execution runs for auditability.
• Ensure model metrics are logged to the model runs.
• Ensure model logging, monitoring, and alerting to make sure any failure points are captured, monitored and alerted for support team to investigate or re-run of the model involves running of multiple experiments and choosing the best model (champion challenger) based on the accuracy/error rate of each experiment, ensure this is done in an automated manner.
li>Ensure the model is triggered to run as per the defined schedule. If the process involves executing multiple models feeding each other to produce the final business outcome, orchestrate them to run based on the defined dependencies.
• Define and Maintain the ML Frameworks (Python, R & MATLAB templates) with any common reusable code that might emerge as part of model developments/operationalisation for future
• models to benefit.
• Where applicable, capture data drift, concept drift, model performance degradation signals and ensure model retrain.
• Implement CI/CD pipelines for ML models and automate the deployment.
• Maintain relevant documentation.

Requirements:

• Bachelor's degree in a relevant field.
• Minimum of 5 years of experience as a business analyst, with a focus on capturing and documenting business requirements and business processes.
• Strong understanding of banking and financial industry practices and regulations.
• Solid knowledge of Data Management process, data analysis and modelling techniques.
• Experience in monetary policy analysis (nice to have)
• Experience in time series database analysis
• Familiarity with business intelligence tools and concepts.
• Strong analytical and problem-solving skills.
• Experience in managing software development lifecycles within Agile frameworks to ensure timely and high-quality delivery.
• Excellent communication and collaboration skills.
• Ability to adapt to changing requirements and priorities in a fast-paced environment.

Spearheading the integration of machine learning into cutting-edge electronics

This innovative team of engineers and scientists are using machine learning tightly integrated with modern electronics to create new classes of products and radically alter the shape, performance and effectiveness of existing ones. As industry goes through a machine learning revolution you can be here, leading the charge.

You will work across the whole machine learning development lifecycle from initial concepts through data collection, cleaning and preparation to prototyping, testing and evaluation. With your models integrated with leading edge electronics, the final products are fully functional prototypes and demonstrator units manufactured at small scale. What’s special about this group is they do this dozens of times per year working across multiple domains. You can be working on computer vision for one project and generative models for the next. 

Requirements:

• Strong knowledge of Python and its use in machine learning including hands-on experience building products with modern ML frameworks such as TensorFlow and PyTorch
li>Broad knowledge of machine learning techniques across multiple domains and the ability to transition into new domains quickly
• A top degree in a STEM subject
• UK national

While not required, experience deploying machine learning onto a range of hardware from resource constrained embedded systems through to edge computing is desirable. As is any knowledge of GPU programming languages and frameworks (CUDA, ROCm, etc).

Your future colleagues will be similarly highly skilled, with experience across industry and the drive to innovate. You will find yourself in a low-management work environment that encourages teamwork and respect for individuals’ expertise. Benefits include private medical insurance, generous pension scheme and access to local social and sports clubs. Please note, you are required to be onsite full-time for this position.

Another top job from ECM, the high-tech recruitment experts.    

Even if this job's not quite right, do contact us now - we may well have the ideal job for you. To discuss your requirements call (phone number removed) or email your CV. We will always ask before forwarding your CV.

Please apply (quoting ref: CV27413 ) only if you are eligible to live and work in the UK. By submitting your details you certify that the information you provide is accurate.

Role: Machine Learning Operations Engineer
Location: Oxfordshire
Salary: 65,000 - 75,000

This is an exciting opportunity to join a world leading company specialising in motion capture and tracking systems, with products used globally in the entertainment, engineering, and life sciences sectors. My Client are looking for a talented Machine Learning Operations Engineer to support and enhance their cutting edge machine learning capabilities.

The Role

You will join a collaborative Research and Development team based in Oxford, contributing to the development and maintenance of a modern ML operations stack. This includes data acquisition pipelines, data management, and machine learning model training infrastructure. The environment includes both self-managed on premise systems and cloud-based infrastructure, primarily using AWS.

You will have the opportunity to influence the technical direction of the ML Ops team, propose new areas for development, and potentially lead your own projects.

This is a hybrid role combining remote and on site working. There is no expectation to be available outside core business hours.

Key Responsibilities

• Maintain and improve ML Ops infrastructure
• Manage on premise Kubernetes clusters and ML pipelines
• Integrate ML toolkits into operational workflows
• Collaborate with ML developers to streamline workflows
• Suggest and implement technical improvements and new tools

Required Skills and Experience

• Academic background (research Masters level) or industry experience in a relevant field
• Strong experience managing on premise Kubernetes clusters
• Deep knowledge of Kubeflow or similar systems such as MLflow
• Proficient in Python and experienced with Linux systems
• Familiar with AWS services such as Cognito, S3, EC2 and Lambda
• Experience working with ML frameworks such as PyTorch or Lightning
• Capable of designing and delivering ML Ops solutions across various platforms

Desirable Skills

• Background in DevOps with experience in CI systems such as Jenkins
• Familiarity with infrastructure as code tools such as Ansible
• Interest in human motion capture, sports tech, or animation
• Exposure to C++ is a bonus

Benefits

• 65,000 - 75,000 (DOE)
• 10 percent company pension
• 25 days annual leave plus bank holidays
• Life assurance
• Private medical insurance including dental and optical
• Permanent health insurance
• Cycle to work scheme
• Free on site parking

WR Engineering are the #1 recruitment partner for engineering, manufacturing & technical sales jobs. We recruit for permanent and contract jobs UK wide.

WR is acting as an Employment Agency in relation to this vacancy.