Benefits:

• Competitive salary, benchmarked against the market and reviewed annually

• Company share programme

• Hybrid and/or flexible work arrangements

• An outstanding £3,000 flexible benefits including private medical insurance, critical illness coverage, life assurance, EAP, group income protection

• Funded relocation support

Education Requirements:

• PhD in related field (Mech Eng, Aerospace, Comp Science, Robotics, Mechatronics) with 2+ years of professional experience is desired

• MS in related field (Mech Eng, Aerospace, Comp Science, Robotics, Mechatronics) with 4+ years of professional experience is acceptable

Experience Requirements:

• Extensive hands-on experience of optimisation-based trajectory planning

• Experience with sampling-based trajectory planning approaches

• Experience with trajectory planning problem formulation and problem transcription

• Modern C++ algorithm development and deployment, ideally in a production environment (including STL and common testing frameworks)

Responsibilities:

• Collaborate with your Team Lead and team members to solve Spatio-Temporal motion planning problems, including off-the-shelf solver evaluation and custom solver implementation.

• Collaborate with the Decision Making team to transcribe nuanced manoeuvres in complex on- and off-road environments into generalised Trajectory Planning problems.

• Collaborate with the Controls team to ensure Smooth, Comfortable, Precise manoeuvre execution for on- and off-road applications.

• Contribute to the development of high quality functionality and APIs that allow the Planner functionality to be used as a building block for on-vehicle capabilities.

• Create appropriate metrics and tools to measure and benchmark the performance of Planners deployed on various AV platforms.

Benefits:

• Competitive salary, benchmarked against the market and reviewed annually

• Company share programme

• Hybrid and/or flexible work arrangements

• An outstanding £3,000 flexible benefits including private medical insurance, critical illness coverage, life assurance, EAP, group income protection

• Funded relocation support

Education Requirements:

• Degree in Computer Science, Mathematics or a related field.

• 3+ years of professional experience developing behavioural machine learning technologies for autonomous vehicles or robotics.

• Experience with production ML pipelines: data creation and curation, training frameworks, evaluation pipelines.

• Fluency in Python and experience with data analysis libraries and packages.

• Proven record of leading and delivering projects as part of a team.

Responsibilities:

• Take a leading role within your team to develop and deploy state of the art data pipelines for our machine learning models.

• Design and implement metrics for model validation and continuous monitoring in production.

• Leverage the Oxa Metadriver™ platform to generate synthetic data, and train effective and robust driving policies,

• Build cloud tooling and infrastructure in support of experimentation, evaluation and deployment workflows.

• Engage with team members and colleagues throughout the business to create an environment that supports collaboration and mutual understanding.

Benefits:

• Competitive salary, benchmarked against the market and reviewed annually

• Hybrid working arrangements

• Life Insurance

• AD&D Insurance

• Long Term Disability Insurance

Education Requirements:

• Degree in Robotics or a related field (e.g., Computer Science, Engineering, Physics, etc.)

Experience Requirements:

• Solid foundational knowledge of Robotics technologies and how they operate

• Extensive experience designing, developing and maintaining pipelines and tools to measure real-time engineering operations and processes

• Strong analytical and problem-solving skills in performing statistical analysis, data modeling, and predictive analytics.

• Professional experience in modern C++, including the STL and common testing frameworks

• Fluency in Python for software development

Responsibilities:

• Developing and maintaining high quality processes and APIs to generate performance signals and combine them to create meaningful performance metrics

• Building and owning the necessary tools and the Planning evaluation framework

• Contributing significantly to the engineering lifecycle, including scoping, design, implementation, testing, deployment and maintenance of your team's work

• Verifying and validating through on-road testing and scenario simulation

• Leveraging synthetic data from simulations to expand test situations

Benefits:

• Competitive salary, benchmarked against the market and reviewed annually

• Hybrid and/or flexible work arrangements

• An outstanding £3,000 flexible benefits including private medical insurance, critical illness coverage, life assurance, EAP, group income protection

• A salary exchange pension plan

• 25 days’ annual leave plus bank holidays

Education Requirements:

• Solid experience in embedded systems network engineering.

• Proficiency in Embedded Linux, experience with kernel development, device drivers, and real-time operating systems (RTOS)

• Ability to work at scale (Automation and traceable deployment)

• Deep knowledge of Unix/Linux Network stacks and diagnostics.

• Hands-on experience with embedded computers and controllers, preferably in automotive or robotics.

Responsibilities:

• Developing AV network architecture and solutions with the cutting edge automotive grade sensors and computers

• Designing reference network topology and configurations for different types of autonomous vehicles.

• Developing diagnostic features to monitor network health (performance, degradation, fault detection). Developing system plugins to allow the autonomous system to make informed safety decisions on the basis of network health.

• Analysing network issues and improving network traffic stability and performance.

• Networking implementation, configure and maintain network interfaces for communication between vehicle computers, sensors, and cloud services.

Benefits:

• Competitive salary, benchmarked against the market and reviewed annually

• Hybrid and/or flexible work arrangements

• An outstanding £2,000 flexible benefits including private medical insurance, critical illness coverage, life assurance, EAP, group income protection

• A salary exchange pension plan

• 25 days’ annual leave plus bank holidays

Education Requirements:

• Recent experience working in a people centric role, ideally in a HR or people team

• Solid, detail orientated administration acumen.

• High proficiency in Google Workspace: Docs, Sheets, Gmail.

• Exposure to working with HRIS and ATS systems.

• Strong communication and interpersonal skills

Responsibilities:

• Onboarding administration such as: Drafting and issuing offer letters and contracts of employment. Issuing new starter documents, collating and recording documents received and liaising with new starters. Conducting reference, pre-employment checks and right to work checks. Liaising with line managers and IT to facilitate onboarding. Conducting HR Inductions for new starters. Monitoring completion of the probation period process.

• Administration of internal HR Information System (HRIS) including workflows, system set up and settings.

• Supporting activities related to the creation, update and compilation of people data and reports.

• Act as the employee interface for people queries within the HR inbox.

• Assisting with administration of family friendly, annual leave and time off policies.

Benefits:

• Competitive salary, benchmarked against the market and reviewed annually

• Company share programme

• Hybrid and/or flexible work arrangements

• Core benefits of market leading private healthcare, life assurance, critical illness cover, income protection, alongside a company paid health cash plan (including gym discounts)

• A flexible £2,000 (pro-rata) benefits fund to spend on additional benefits of your choice, including tech scheme and cycle to work benefits

Education Requirements:

• Experience with Machine Learning in a research environment.

• Demonstrate proficiency in Python software development skills

• Experience with computer vision and robotics. More specifically object detection, tracking and localization.

• Solid software engineering design principles and up-to-date knowledge of Python best practices

• An ability to understand both technical and commercial requirements.

Responsibilities:

• Researching and developing state of the art pipelines for: analysing deployment domains, route feasibility checks, domain clustering and classification, representation learning and data coverage analysis.

• Researching and developing state of the art techniques and processes for assuring pre- and post-deployment data coverage across the company.

• Responsible for data interpretation, data governance, communicating findings from the validation, and creating dashboards for metrics management.

• Keeping up with the latest advances in computer vision and tracking research and applying relevant techniques to Oxa MetaDriver

• Contributing to the development tools and processes to support a common testing framework across the company, acquisition of data, ML frameworks and commercial operations

Benefits:

• Competitive salary, benchmarked against the market and reviewed annually

• Hybrid and/or flexible work arrangements

• An outstanding £3,000 flexible benefits including private medical insurance, critical illness coverage, life assurance, EAP, group income protection

• A salary exchange pension plan

• 25 days’ annual leave plus bank holidays

Education Requirements:

• Proven expertise in the engineering of embedded systems networks.

• Experience in scaling operations through automation and deployable solutions with traceability.

• In-depth understanding of Unix/Linux network architectures and diagnostics.

• Background in handling time-sensitive packet delivery systems.

• Familiarity with cellular modem connectivity.

Responsibilities:

• Crafting cutting-edge network architecture and solutions using advanced automotive-grade sensors and computers.

• Designing exemplary network topologies and configurations tailored for various types of autonomous vehicles.

• Creating diagnostic features to monitor network health, focusing on performance, degradation, and fault detection. Additionally, developing system plugins that empower the autonomous system to make informed safety decisions based on the health of the network.

• Investigating network issues and enhancing stability and performance to streamline network traffic.

• Collaborating with stakeholders across the organization to grasp requirements and provide essential tools for vehicle commissioning, configuration, and synchronization