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Day 92
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Cambridge Office, United Kingdom
Open 3 months, first seen by us 92 days agoYou will be responsible for exploring solutions to interesting problems in a variety of domains, using techniques including language models, neural networks, statistical methods, and classical machine learning where appropriate. You will work both as an independent researcher and in team collaborations. You will also be responsible for implementing your machine learning models in the wider software stack. As we deploy our machine learning models in a variety of settings, including on edge devices, you will be expected to produce optimised solutions for both latency and memory. Please note this is a hybrid role, with a compulsory attendance of 2 days a week in the Cambridge office. What experience do I need?Read the full posting
Employment type in the employer’s posting: Full timeFrom the employer’s posting
Explore solutions to varied problems using language models, neural networks and statistical methods
Implement machine learning models in the wider software stack
Produce models optimised for latency and memory, including on edge devices
Test and implement research outcomes with software engineers
exploring solutions to interesting problems in a variety of domains, using techniques including language models, neural networks, statistical methods, and classical machine learning where appropriate
You will also be responsible for implementing your machine learning models in the wider software stack.
you will be expected to produce optimised solutions for both latency and memory
Collaborating with software engineers, you'll test and implement research outcomes
Candidates must have a PhD or master's degree in machine learning or a related discipline or equivalent experience.
Experience with Python machine learning libraries (e.g. PyTorch, TensorFlow, scikit-learn)
Experience with a variety of machine learning techniques.
Be a team player but with the ability to operate autonomously and take independent decisions.
Essential: - Candidates must have a PhD or master's degree in machine learning or a related discipline or equivalent experience. - Experience with Python machine learning libraries (e.g. PyTorch, TensorFlow, scikit-learn)
Open 3 monthsWe first saw this posting 92 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 92
Up longer than most. Similar jobs usually come down between day 6 and day 70.
From 4,474 similar postings that came down. Coming down is not always a hire.
2 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordAdd your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Candidates must have a PhD or master's degree in machine learning or a related discipline or equivalent experience. - Experience with Python machine learning libraries (e.g. PyTorch, TensorFlow, scikit-learn) - Experience with a variety of machine learning techniques.
Complete your application on darktrace.wd3.myworkdayjobs.com. The employer’s form will show what is required.
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New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Darktrace is a global leader in AI-driven cybersecurity, helping organizations stay ahead of evolving threats every day.
Darktrace was built on a genuinely differentiated idea: that Adaptive AI could detect and respond to novel, real-time cyber threats. That approach matters more than ever in the era of AI. Today, our customers depend on us to stay ahead.
At Darktrace, we are energized by that responsibility. We work across teams and rally around a shared goal. We own outcomes end to end - step in, step up and see things through without waiting to be asked. We make decisions with urgency, say the hard thing, and hold each other to high standards with care and directness. We move first and learn fast anticipating where our customers are going next, continuously challenging ourselves.
We invest in the skills, learning and opportunities that help people deliver at the level their roles demand, and reward the aptitude and curiosity to grow beyond them.
Our Values: Own It | Win as One | Raise Our Bar | Move First. Learn Fast
Job Description:
Darktrace is a global leader in AI for cybersecurity that keeps organisations ahead of the changing threat landscape every day. Founded in 2013, Darktrace provides the essential cybersecurity platform protecting nearly 10,000 organisations from unknown threats using its proprietary AI.
The Darktrace Active AI Security Platform™ delivers a proactive approach to cyber resilience to secure the business across the entire digital estate – from network to cloud to email. Breakthrough innovations from our R&D teams have resulted in over 200 patent applications filed. Darktrace’s platform and services are supported by over 2,400 employees around the world. To learn more, visit http://www.darktrace.com.
As a Machine Learning Researcher, you'll play a key role in diverse projects, from prototyping new ideas to improving existing projects. Collaborating with software engineers, you'll test and implement research outcomes, contributing to our distinctive cyber defence methodology. This position emphasises expertise in machine learning, though will also involve extensive collaboration with software development and security analysis teams.
What will I be doing?
You will be responsible for exploring solutions to interesting problems in a variety of domains, using techniques including language models, neural networks, statistical methods, and classical machine learning where appropriate. You will work both as an independent researcher and in team collaborations. You will also be responsible for implementing your machine learning models in the wider software stack. As we deploy our machine learning models in a variety of settings, including on edge devices, you will be expected to produce optimised solutions for both latency and memory.
Please note this is a hybrid role, with a compulsory attendance of 2 days a week in the Cambridge office.
What experience do I need?
We are looking for a curious and motivated machine learning professional with a strong academic or industry background in AI, machine learning, or a related field. You will be comfortable applying machine learning techniques to solve complex real-world problems, working collaboratively within a multidisciplinary team, and communicating technical concepts to a range of stakeholders. A proactive approach to learning, problem-solving, and innovation will be key to success in this role.
Essential:
Desirable:
Benefits:
23 days’ holiday + all public holidays, rising to 25 days after 2 years of service,
Additional day off for your birthday,
Private medical insurance which covers you, your cohabiting partner and children,
Life insurance of 4 times your base salary,
Salary sacrifice pension scheme,
Enhanced family leave,
Confidential Employee Assistance Program,
Cycle to work scheme.
As a growing business strengthening its governance and controls, this role plays a part in supporting high standards of integrity and accountability.


Darktrace is an Equal Opportunity Employer. We consider all qualified applicants for employment without regard to race, color, religion, sex (including pregnancy, childbirth, and related medical conditions), sexual orientation, gender identity or expression, national origin, age, disability, genetic information, marital status, veteran or military status, or any other characteristic protected by applicable federal, state, or local law.
Darktrace is committed to providing reasonable accommodations to qualified individuals with disabilities in accordance with applicable laws. If you require a reasonable accommodation to participate in the application or interview process, please contact your Talent Partner.
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Cambridge Office, United Kingdom
You will be responsible for exploring solutions to interesting problems in a variety of domains, using techniques including language models, neural networks, statistical methods, and classical machine learning where appropriate. You will work both as an independent researcher and in team collaborations. You will also be responsible for implementing your machine learning models in the wider software stack. As we deploy our machine learning models in a variety of settings, including on edge devices, you will be expected to produce optimised solutions for both latency and memory. Please note this is a hybrid role, with a compulsory attendance of 2 days a week in the Cambridge office. What experience do I need?
No clear work-authorization passage found. Eligibility is unconfirmed.