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- Tasks: Build scalable ML tools and collaborate with a dynamic team on innovative projects.
- Company: Leading tech company focused on AR/VR solutions and cutting-edge research.
- Benefits: Competitive salary, flexible work options, and opportunities for continuous learning.
- Why this job: Join us to shape the future of technology and make a real impact in ML.
- Qualifications: 4+ years in Python and deep learning frameworks; strong problem-solving skills required.
- Other info: Exciting environment with opportunities to work on complex, real-world data challenges.
The predicted salary is between 36000 - 60000 £ per year.
Responsibilities:
- Create robust, flexible and scalable ML tooling and infrastructure which supports research scientists to leverage the company's powerful infrastructure (through e.g. source control, distributed compute clusters, data storage).
- Work collaboratively as part of a multifunctional team where communication, documentation and teamwork are highly valued.
- Write clean, maintainable code, debug complex problems that span systems, prioritise ruthlessly and get things done with a high level of efficiency.
- Coordinate with a large set of internal infrastructure and tool teams across the lab and across the company to evaluate and integrate with existing systems.
- Learn constantly, dive into new areas with unfamiliar technologies, and embrace the ambiguity of AR/VR problem solving.
Requirements:
- Bachelor's degree in Computer Science or related field, or equivalent work experience.
- 4+ years industry experience with deep learning frameworks in Python, such as PyTorch or TensorFlow.
- 2+ years industry experience working with large, complex data sets for machine learning, including capture and annotation.
- Demonstrated experience implementing and evaluating working and end-to-end prototypical learning systems.
- Experience working with high performance or distributed compute solutions.
- Deployment and continuous integration experience.
Preferred Qualifications:
- Familiarity with Machine Learning for Audio, multimodal or DSP purposes.
- Experience writing scalable ML tooling/pipelines for use by researchers.
- Experience in Linux or Windows shell scripting.
- Ability to gather requirements and work closely with researchers to develop novel solutions.
- History of writing code to support the execution of research initiatives.
Top 3 must-have HARD skills:
- Python and infrastructure focused software engineers.
- PyTorch or similar AI/ML engines.
- Distributed infrastructure.
Good to have skills:
- Working with complex, real-world multimodal data.
- Audio collaboration with research users/customers to deliver robust and stable tooling to address their needs.
Experience:
- 4+ years of industry experience writing Python / ML code.
Story Behind the Need:
- Backfilling a role for an ML pipeline-focused software engineer, focusing on efficient and scalable infrastructure, and ML frameworks and tooling.
Machine Learning Engineer in London employer: Templeton & Partners - Innovative & Inclusive Hiring Solutions
Contact Detail:
Templeton & Partners - Innovative & Inclusive Hiring Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups or webinars, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python and ML frameworks like PyTorch or TensorFlow. This gives you a chance to demonstrate your expertise and makes you stand out from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your problem-solving skills. Be ready to discuss your experience with complex data sets and how you've tackled challenges in previous roles. Practice coding problems and system design questions to impress your interviewers.
✨Tip Number 4
Don’t forget to apply through our website! We love seeing applications directly from candidates who are passionate about joining our team. Plus, it shows you're proactive and genuinely interested in the role.
We think you need these skills to ace Machine Learning Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python and ML frameworks like PyTorch or TensorFlow. We want to see how your skills align with the responsibilities listed in the job description, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about machine learning and how your background makes you a great fit for our team. We love seeing enthusiasm and a bit of personality!
Showcase Your Problem-Solving Skills: In your application, mention specific examples where you've debugged complex problems or worked with large datasets. We value efficiency and creativity, so let us know how you’ve tackled challenges in the past!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team at StudySmarter!
How to prepare for a job interview at Templeton & Partners - Innovative & Inclusive Hiring Solutions
✨Know Your Tech Inside Out
Make sure you’re well-versed in Python and the deep learning frameworks like PyTorch or TensorFlow. Brush up on your knowledge of distributed infrastructure and be ready to discuss how you've used these technologies in past projects.
✨Showcase Your Problem-Solving Skills
Prepare to talk about complex problems you've debugged and how you approached them. Use specific examples that highlight your ability to prioritise tasks and get things done efficiently, especially in a collaborative environment.
✨Emphasise Teamwork and Communication
Since this role values collaboration, think of instances where you’ve worked with multifunctional teams. Be ready to discuss how you communicated effectively and documented your work to support your colleagues.
✨Demonstrate Your Learning Mindset
Be prepared to share experiences where you had to dive into unfamiliar technologies or tackle ambiguous problems. Highlight your eagerness to learn and adapt, especially in the context of AR/VR or machine learning.
