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- Tasks: Lead innovative video AI/ML projects and transform sports technology insights.
- Company: Join a dynamic sports-tech company based in London with a focus on cutting-edge technology.
- Benefits: Enjoy flexible working options, professional growth opportunities, and an inclusive environment.
- Why this job: Be at the forefront of sports tech, making a real impact with your skills and creativity.
- Qualifications: Advanced AI/ML expertise, technical leadership, and cloud/edge inference experience required.
- Other info: Don't let imposter syndrome hold you back—apply anyway!
The predicted salary is between 48000 - 84000 £ per year.
Staff Machine Learning Engineer (Applied Vision) Sports-Tech | London HQ | Flexible Working / Remote Working Role Highlights Lead cutting-edge video AI/ML projects Transform sports technology insights Build scalable machine learning systems Key Requirements Advanced AI/ML product expertise Technical leadership skills Cloud/edge inference experience Exceptional communication Nice-to-Have Sports tech background Compensation is Competive We Offer Flexible work Professional growth Inclusive environment Imposter syndrome? Apply anyway!
Staff Machine Learning Engineer (Applied Vision) employer: Understanding Recruitment
Contact Detail:
Understanding Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Staff Machine Learning Engineer (Applied Vision)
✨Tip Number 1
Make sure to showcase your experience with AI/ML projects in your conversations. Highlight specific examples where you've led projects or made significant contributions, especially in the sports tech domain.
✨Tip Number 2
Demonstrate your technical leadership skills during interviews. Be prepared to discuss how you've guided teams through complex challenges and how you foster collaboration among team members.
✨Tip Number 3
Familiarize yourself with cloud and edge inference technologies. Being able to discuss your hands-on experience with these systems will set you apart from other candidates.
✨Tip Number 4
Communicate your passion for sports technology clearly. Whether it's through personal projects or professional experiences, showing your enthusiasm for the industry can make a strong impression.
We think you need these skills to ace Staff Machine Learning Engineer (Applied Vision)
Some tips for your application 🫡
Highlight Your Expertise: Make sure to emphasize your advanced AI/ML product expertise in your application. Provide specific examples of projects you've led or contributed to, especially those related to video AI/ML.
Showcase Technical Leadership: Demonstrate your technical leadership skills by detailing experiences where you guided a team or influenced project outcomes. This will help the company see your potential for leading cutting-edge projects.
Communicate Clearly: Since exceptional communication is a key requirement, ensure that your application is well-structured and free of jargon. Use clear language to convey your ideas and experiences.
Express Your Interest in Sports Tech: If you have any experience or passion for sports technology, make sure to mention it. Even if it's not a strict requirement, showing enthusiasm for the field can set you apart from other candidates.
How to prepare for a job interview at Understanding Recruitment
✨Showcase Your AI/ML Expertise
Be prepared to discuss your previous projects in AI and machine learning, especially those related to video processing. Highlight specific challenges you faced and how you overcame them.
✨Demonstrate Technical Leadership
Share examples of how you've led teams or projects in the past. Discuss your approach to mentoring others and fostering collaboration within a technical environment.
✨Communicate Clearly and Effectively
Since exceptional communication is a key requirement, practice explaining complex technical concepts in simple terms. This will show your ability to convey ideas to both technical and non-technical stakeholders.
✨Connect with Sports Technology
If you have any experience or passion for sports tech, make sure to bring it up during the interview. Relating your background to the company's focus can set you apart from other candidates.
