At a Glance
- Tasks: Use machine learning to combat cybercrime and develop innovative classification systems.
- Company: Join Netcraft, a leader in cybercrime detection with a supportive team culture.
- Benefits: Enjoy 33 days of leave, private health cover, and flexible working options.
- Other info: Diversity and inclusion are key; we welcome applicants from all backgrounds.
- Why this job: Make a real impact in the fight against cybercrime while growing your skills.
- Qualifications: Strong web fundamentals and a basic understanding of machine learning required.
The predicted salary is between 56700 - 69300 £ per year.
About Netcraft
Netcraft is the global leader in cybercrime detection and disruption.
We’re a trusted partner for three of the four largest companies in the world and many large governments.
We’ve blocked over 225 million cyber-attacks to date, and we take down around 33% of the world’s phishing attacks.
About Netcraft
Netcraft is the global leader in cybercrime detection and disruption.
We’re a trusted partner for three of the four largest companies in the world and many large governments.
We’ve blocked over 225 million cyber-attacks to date, and we take down around 33% of the world’s phishing attacks.
Our purpose and passion are focused on just one thing: protecting the world from cybercrime.
That passion shapes how we work, too.
We’re proud of our talented team and the value each person brings, and we’ve built a workplace where people feel supported and inspired.
From strong benefits and wellness programs to meaningful collaboration and team connection.
The role
We are looking for an engineer who wants to apply ML to a real adversarial problem, where attackers actively evolve to evade you and turn to increasingly complicated schemes.
As part of the Novel Classification team, you’ll use machine learning and AI to identify fraudulent content on the Internet, from phishing sites to the full breadth of online scams.
You’ll learn from experienced engineers and see your ideas in production within weeks, driving the automated blocking and takedowns that disrupt cybercrime at scale.
Recent projects include multi-modal embeddings that power classification and search, LLM classifiers, computer vision models for logo detection, and ensemble predictors that combine visual and semantic signals.
We keep a close eye on the field and adopt new models and techniques early when they look promising.
You’ll work across the full lifecycle: training and evaluating models, serving them on our GPU‑backed Kubernetes clusters, wiring them into production classification systems, and watching how they behave against live attack traffic.
Day to day, you’ll be
- Building, evaluating and tuning the classifiers that decide what gets blocked and taken down.
- Deploying and operating model serving infrastructure on Kubernetes, including LLM inference (e. g. v LLM).
- Optimising models for high‑volume, low‑cost serving.
- Running experiments against live data, measuring precision, recall and false positive rates, and using the results to decide what ships.
- Integrating models into our production classification platforms.
- Building the pipelines and monitoring behind the models: feature extraction, scheduled retraining, experiment tracking, and the metrics that prove a solution works.
- Investigating and fixing issues in production, from model regressions to performance bottlenecks.
- Working across the business with engineers and analysts who depend on our classifiers.
- What you’ll need to be successful
- Strong web fundamentals: HTTP, DNS, and above all how websites work, from request to rendered page.
You’ll use them both to understand the resources we classify and to build high‑performance webservers.
- A working understanding of machine learning fundamentals, such as training, evaluation, overfitting and precision/recall trade‑offs.
This could come from industry, research or substantial personal projects.
- Good written and verbal communication skills.
The work the team does is complex, and we must be able to articulate the impact of our work clearly and concisely, to a wide range of stakeholders.
- An empirical mindset. You design experiments, measure outcomes, and use metrics to validate and demonstrate impact.
- Willingness to learn Go and modern Perl, including asynchronous programming.
- Strong attention to detail and a real sense of responsibility. Customers act on our classifications, and Netcraft’s reputation depends on getting them right.
- Bonus points if you have
- A keen interest in cybercrime or cybersecurity.
- Experience fine‑tuning models, including evaluation.
- Experience with LLM agents, evaluation & serving (e. g. v LLM or llama. cpp).
- Familiarity with cloud‑native technologies such as Kubernetes, Flux, Argo and API gateways.
- Experience with multi‑modal models, embeddings or similarity search at scale.
- Experience with ML experiment tracking and workflow tooling, such as MLflow or Argo Workflows.
- Experience with SQL databases, including writing and optimising queries against large datasets.
Preferably based in London, though Manchester and Bath are also options.
At Netcraft we strongly believe in individual growth and development.
Even if you can’t tick every box above right now, please don’t let it put you off applying.
- The Reward Package
- 33 days annual leave - includes public holidays which can be worked if you prefer
- Generous enhanced family leave and pay
- Enhanced company sick pay from day one of employment, with additional support after your first six months’ service
- Salary sacrifice pension with matched employer contributions up to 5% + NI savings
- Private health cover, including access to a private GP service
- Life Assurance at 4 x salary
- Equity tracking scheme (eligibility criteria apply) - allowing you share in Netcraft's long term success
- Hybrid and flexible working options
- Meals, snacks, and drinks provided in the office
- Comprehensive health, safety, and wellness service available 24/7 for you and your family
- Two paid Learning & Development days per year plus access to learning resources such as Udemy and Coursera to support your career
- Two Volunteering Days per year, to allow you to contribute to your wider community or charity
- Employee Referral Bonus scheme
- Spot reward bonus scheme to reward truly outstanding contributions
- Diversity, Equity & Inclusion
This is deeply important to us.
Through our ally network, we support under‑represented groups and maintain a working environment free from bias, harassment, or discrimination.
We encourage candidates from all backgrounds to apply.
We’re also happy to make adjustments to the hiring process to ensure every candidate can participate fully.
Please note
Netcraft does not accept unsolicited approaches from external recruiters.
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Software Engineer (Machine Learning) employer: netcraft
Netcraft is an exceptional employer, dedicated to fostering a supportive and inspiring work environment where innovation thrives. With a strong focus on employee well-being, we offer generous benefits such as 33 days of annual leave, private health cover, and opportunities for professional growth through learning resources and volunteering days. Our commitment to diversity, equity, and inclusion ensures that every team member feels valued and empowered to contribute to our mission of protecting the world from cybercrime.
StudySmarter Expert Advice🤫
We think this is how you could land Software Engineer (Machine Learning)
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We think you need these skills to ace Software Engineer (Machine Learning)
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at netcraft.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at netcraft and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at netcraft
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If netcraft uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.