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- Tasks: Join us to tackle exciting computer vision challenges and develop innovative software solutions.
- Company: Humand Talent is at the forefront of AI, shaping technology across various industries.
- Benefits: Enjoy private medical cover, life insurance, free parking, and more perks!
- Why this job: Be part of a diverse team pushing the boundaries of motion capture and computer vision.
- Qualifications: Strong background in computer vision and machine learning; Python and PyTorch experience required.
- Other info: We celebrate diversity and welcome applicants from all backgrounds.
The predicted salary is between 43200 - 72000 £ per year.
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This range is provided by Humand Talent. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Base pay range
Direct message the job poster from Humand Talent
Are you ready to push the boundaries of computer vision and machine learning?
We’re looking for a talented Machine Learning Engineer to join an innovative team developing high-performance software and cutting-edge hardware used across entertainment, engineering, medical, sports and many more.
In this role, you’ll be part of a collaborative research and development environment, working on challenging computer vision problems and delivering solutions that power real-world applications.
What you’ll be doing:
- Tackling computer vision challenges such as object detection, human pose estimation, and modelling shape, appearance, and movement.
- Applying advanced ML methods (CNNs, ViTs) alongside non-ML algorithms.
- Working with large spatio-temporal datasets.
- Taking projects from research prototypes through to production.
- Collaborating with a skilled, multidisciplinary team in a hybrid setup.
What we’re looking for:
- Strong academic (research Masters/PhD) or equivalent industry experience in computer vision & machine learning.
- Proven track record applying ML techniques to solve vision problems.
- Python, PyTorch, and Lightning experience essential; C++ a bonus.
- Experience with model optimisation (e.g., quantisation for GPUs) is desirable.
- A proactive, collaborative mindset with a passion for innovation.
What’s on offer:
- Private medical cover (including optical & dental)
- Life cover & permanent health insurance
- Free on-site parking and many more…
If you want to be part of a forward-thinking team shaping the future of motion capture and computer vision, we’d love to hear from you.
Diversity & Inclusion
Humand Talent and our client believe that innovation is stronger when built by diverse teams. We’re proud to support equal opportunity for all, and welcome applicants regardless of age, disability, gender identity, race, religion or belief, sex, sexual orientation, or background. We celebrate difference – and we want to hear from you.
Seniority level
- Seniority levelMid-Senior level
Employment type
- Employment typeFull-time
Job function
- Job functionEngineering and Information Technology
- IndustriesTechnology, Information and Media
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Machine Learning Engineer ID42778 employer: Humand Talent
Contact Detail:
Humand Talent Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer ID42778
✨Tip Number 1
Familiarise yourself with the latest advancements in computer vision and machine learning. Follow relevant research papers, attend webinars, and engage in online forums to stay updated. This knowledge will not only help you during interviews but also demonstrate your passion for the field.
✨Tip Number 2
Build a portfolio showcasing your projects related to object detection, human pose estimation, or any other relevant ML applications. Having tangible examples of your work can set you apart from other candidates and provide talking points during interviews.
✨Tip Number 3
Network with professionals in the industry, especially those working in computer vision and machine learning. Attend meetups, conferences, or online events to connect with potential colleagues or mentors who can provide insights and possibly refer you to job openings.
✨Tip Number 4
Prepare for technical interviews by practising coding challenges and algorithm problems, particularly in Python and C++. Familiarity with frameworks like PyTorch and Lightning is crucial, so consider working on small projects that utilise these tools to enhance your skills.
We think you need these skills to ace Machine Learning Engineer ID42778
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with computer vision and machine learning. Include specific projects where you've applied ML techniques, especially those involving object detection or human pose estimation.
Craft a Strong Cover Letter: In your cover letter, express your passion for innovation and collaboration. Mention your experience with Python, PyTorch, and any relevant projects that demonstrate your ability to tackle complex challenges in ML.
Showcase Relevant Skills: Clearly list your technical skills, particularly in ML methods like CNNs and ViTs. If you have experience with model optimisation or C++, make sure to highlight these as they are desirable for the role.
Prepare for Technical Questions: Be ready to discuss your previous work in detail, especially how you've taken projects from research prototypes to production. Think about specific challenges you've faced and how you overcame them using your skills.
How to prepare for a job interview at Humand Talent
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, PyTorch, and Lightning in detail. Bring examples of projects where you've applied these technologies, especially in computer vision tasks like object detection or human pose estimation.
✨Demonstrate Problem-Solving Abilities
Expect to tackle hypothetical scenarios or case studies during the interview. Practice explaining your thought process for solving complex computer vision problems, highlighting your approach to research prototypes and production.
✨Highlight Collaboration Experience
Since the role involves working in a multidisciplinary team, be ready to share examples of how you've successfully collaborated with others. Discuss any experiences that showcase your proactive mindset and ability to innovate within a team setting.
✨Prepare for Questions on Model Optimisation
Familiarise yourself with model optimisation techniques, such as quantisation for GPUs. Be ready to explain how you've implemented these methods in past projects and their impact on performance.