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1,380

Data Scientist jobs in United Kingdom

Staff Machine Learning Engineer, Inference Optimisation London, United Kingdom

Wayve Technologies Ltd.

City of London
On-site
GBP 70,000 - 100,000
30+ days ago
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Senior Machine Learning Engineer - FTC

Methodfi

City of London
Hybrid
GBP 50,000 - 80,000
30+ days ago

Temporary GCP Data Engineer

Ki Insurance

City of London
On-site
GBP 60,000 - 80,000
30+ days ago

AI Data Engineer

Snyk Ltd.

City of London
On-site
GBP 65,000 - 85,000
30+ days ago

GIS Data Engineer

RMSI Pvt. Ltd.

Reading
On-site
GBP 60,000 - 80,000
30+ days ago
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Data Engineer (remote)

Acrisure, LLC

Tandridge
Hybrid
GBP 40,000 - 60,000
30+ days ago

Senior Software Engineer - Data Search

Woven by Toyota, Inc.

City of London
Hybrid
GBP 70,000 - 90,000
30+ days ago

Data Analyst

Assystem GmbH

Bristol
Hybrid
GBP 100,000 - 125,000
30+ days ago
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Machine Learning Engineer

Methodfi

City of London
On-site
GBP 50,000 - 70,000
30+ days ago

Junior Data Analyst

Encinos Kapital

City of London
On-site
GBP 30,000 - 40,000
30+ days ago

Entry-Level IT PMO/PSO Analyst - Data & Dashboards

SEFE Marketing & Trading Ltd

City of London
On-site
GBP 35,000 - 45,000
30+ days ago

Senior Machine Learning Engineer, Data for Embodied AI London, United Kingdom

Wayve Technologies Ltd.

City of London
On-site
GBP 80,000 - 100,000
30+ days ago

Software Engineer - (Machine Learning Experience a plus) - hybrid

FactSet Research Systems Inc.

City of London
Hybrid
GBP 60,000 - 80,000
30+ days ago

Data Engineer - AcquiTech

Methodfi

City of London
Hybrid
GBP 50,000 - 80,000
30+ days ago

Data Engineer - AcquiTech

Methodfi

City of London
Hybrid
GBP 50,000 - 80,000
30+ days ago

Junior Machine Learning Engineer (12 Months Fixed Term Contract)

RAPP Worldwide, Inc

City of London
Hybrid
GBP 30,000 - 40,000
30+ days ago

Data Engineer

Systematic, Inc

Farnborough
On-site
GBP 40,000 - 60,000
30+ days ago

AI and Data Engineer

Abyssal S.A

Manchester
Hybrid
GBP 60,000 - 80,000
30+ days ago

Data Engineer - Snowflake

Morgan Stanley

City of London
On-site
GBP 70,000 - 80,000
30+ days ago

Senior Machine Learning Engineer

Isomorphic Labs Limited

City of London
Hybrid
GBP 70,000 - 90,000
30+ days ago

Data Engineer Tech - Development London

DARE

City of London
On-site
GBP 60,000 - 80,000
30+ days ago

Data Engineer

Tickmill UK Ltd

City of London
Hybrid
GBP 60,000 - 80,000
30+ days ago

Cyber GRC / Configuration Management Analyst

Sword group

City of Edinburgh
On-site
GBP 30,000 - 40,000
30+ days ago

Treasury Data Engineer

Jefferies Group LLC

City of London
On-site
GBP 50,000 - 70,000
30+ days ago

Data Engineer

Ki Insurance

City of London
On-site
GBP 60,000 - 80,000
30+ days ago

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Staff Machine Learning Engineer, Inference Optimisation London, United Kingdom
Wayve Technologies Ltd.
City of London
On-site
GBP 70,000 - 100,000
Full time
30+ days ago

Job summary

A leading AI technology firm is seeking a Staff/Principal Machine Learning Engineer to optimize driving models for deployment in consumer vehicles. This role involves developing state-of-the-art ML compression techniques and collaborating with various teams to innovate and deliver on impactful projects. Candidates should have over 5 years of experience in ML optimisation and proficiency in PyTorch. If you are passionate about transforming the future of driving, apply now.

Qualifications

  • 5+ years working as an MLE.
  • Experience working on optimisation problems with hard latency and/or resource constraints.
  • Proficiency with PyTorch.

Responsibilities

  • Develop state of the art techniques in distillation, quantisation, pruning and other ML compression methods.
  • Understand how ML compression methods affect driving behaviour.
  • Stay up to date with latest papers and conferences.
  • Collaborate closely with other model developers and scientists.

Skills

ML compression techniques
PyTorch
Interpersonal skills
Communication skills

Education

PhD in relevant field
Job description

At Wayve we're committed to creating a diverse, fair and respectful culture that is inclusive of everyone based on their unique skills and perspectives, and regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, veteran status, pregnancy or related condition (including breastfeeding) or any other basis as protected by applicable law.

About us

Founded in 2017, Wayve is the leading developer of Embodied AI technology. Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment, enhancing the usability and safety of automated driving systems.

Our vision is to create autonomy that propels the world forward. Our intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving.

In our fast-paced environment big problems ignite us—we embrace uncertainty, leaning into complex challenges to unlock groundbreaking solutions. We aim high and stay humble in our pursuit of excellence, constantly learning and evolving as we pave the way for a smarter, safer future.

At Wayve, your contributions matter. We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact.

Make Wayve the experience that defines your career!

The role

As a Staff/Principal MLE for the ML Optimisation team, you’ll optimise our Driving Model to run efficiently in millions of vehicles with consumer-grade GPUs and accelerators. The focus of this team is to run large transformer-based models efficiently in low-cost, low-power edge devices to enable Wayve’s first driving product - e.g. via methods such as distillation, efficient architectures, pruning, quantisation and others. This is an exciting opportunity to own and lead high impact, early stage projects at Wayve with the ultimate goal of enabling product deployments onto millions of customer vehicles around the world.

Key responsibilities:

  • Develop state of the art techniques in distillation, quantisation, pruning and other ML compression methods to achieve latency, bandwidth and compute targets
  • Understand how ML compression methods affect driving behaviour
  • Stay up to date with latest papers, conferences etc
  • You’ll collaborate closely with other model developers and scientists across the business to drive innovation and delivery
  • You’ll have the opportunity to develop new skills and experience
About you

Essential

  • 5+ years working as an MLE
  • Experience working on optimisation problems with hard latency and/or resource constraints
  • Proficiency with PyTorch
  • Excellent interpersonal and communication skills

Desirable

  • Experience with ML on edge, e.g. automotive, drones, AR/VR, IoT, etc
  • Experience with any of the following: quantisation, distillation, pruning, sparsity methods, NAS, efficient architectures, etc
  • Experience with Nvidia and Qualcomm SoCs and frameworks are valuable, but not required
  • PhD in relevant field, e.g., Computer Science, Machine Learning, Robotics, Engineering, etc.

We understand that everyone has a unique set of skills and experiences and that not everyone will meet all of the requirements listed above. If you’re passionate about self-driving cars and think you have what it takes to make a positive impact on the world, we encourage you to apply.

For more information visit Careeres at Wayve.

To learn more about what drives us, visit Values at Wayve

DISCLAIMER: We will not ask about marriage or pregnancy, care responsibilities or disabilities in any of our job adverts or interviews. However, we do look to capture information about care responsibilities, and disabilities among other diversity information as part of an optional DEI Monitoring form to help us identify areas of improvement in our hiring process and ensure that the process is inclusive and non-discriminatory.

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* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.

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