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- Tasks: Develop innovative machine learning solutions for anomaly detection and glitch detection.
- Company: Global tech-led organisation in the UK with a focus on innovation.
- Benefits: Competitive salary, hybrid work model, and high-impact project opportunities.
- Why this job: Lead research and drive technical direction in cutting-edge machine learning.
- Qualifications: 5+ years experience, strong Python skills, and background in computer vision or applied ML.
- Other info: Collaborative environment with opportunities for professional growth.
The predicted salary is between 43200 - 72000 £ per year.
A global technology-led organization in the UK is looking for a Senior Engineer to develop innovative machine learning solutions with a focus on anomaly and glitch detection. You will drive technical direction, lead research, and collaborate across teams.
The ideal candidate has over 5 years of experience, strong Python skills, and a background in computer vision or applied ML research.
This hybrid position offers a competitive salary and the opportunity to work on high-impact projects.
Staff ML Engineer – Anomaly Detection & Vision at Scale in London employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Staff ML Engineer – Anomaly Detection & Vision at Scale in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those related to anomaly detection and computer vision. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python skills and ML concepts. Practice coding challenges and be ready to discuss your past projects in detail. We want to see how you think and solve problems!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Staff ML Engineer – Anomaly Detection & Vision at Scale in London
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your Python expertise and any relevant experience in machine learning or computer vision. We want to see how your skills align with the role, so don’t hold back!
Tailor Your Application: Customise your CV and cover letter to reflect the specific requirements of the Staff ML Engineer position. We love seeing candidates who take the time to connect their experience with what we’re looking for.
Be Clear and Concise: When writing your application, keep it straightforward and to the point. We appreciate clarity, so make sure your key achievements and experiences shine through without unnecessary fluff.
Apply Through Our Website: We encourage you to submit your application directly through our website. It’s the best way for us to receive your details and ensures you’re considered for this exciting opportunity!
How to prepare for a job interview at Harnham
✨Know Your ML Stuff
Make sure you brush up on your machine learning concepts, especially around anomaly detection and computer vision. Be ready to discuss your past projects in detail, showcasing how you've applied these techniques in real-world scenarios.
✨Showcase Your Python Skills
Since strong Python skills are a must, prepare to demonstrate your coding abilities. You might be asked to solve a problem on the spot, so practice coding challenges related to ML and data manipulation to show off your expertise.
✨Collaboration is Key
This role involves working across teams, so be prepared to discuss your experience in collaborative environments. Share examples of how you've successfully worked with others to drive technical direction and achieve project goals.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare thoughtful questions about the company's approach to machine learning and their current projects. This shows your genuine interest and helps you gauge if the company is the right fit for you.
