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For Companies At a Glance
- Tasks: Create scalable ML tools and collaborate with a dynamic team on innovative projects.
- Company: Join a leading tech company at the forefront of AR/VR technology.
- Benefits: Enjoy healthcare contributions, a pension scheme, and generous annual leave.
- Why this job: Make a real impact in AI/ML while working with cutting-edge technologies.
- Qualifications: 4+ years in deep learning frameworks and experience with complex data sets.
- Other info: Great career progression opportunities for top performers in a supportive environment.
The predicted salary is between 36000 - 60000 £ per year.
Location - Hybrid, Cambridge (3 days in office)
Responsibilities
- Create robust, flexible and scalable ML tooling and infrastructure which supports research scientists to leverage Meta’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 Meta 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.
Benefits
- Healthcare contribution and inclusion in company pension scheme.
- Work laptop and phone.
- 25 days annual leave (pro-rata) plus paid bank holidays.
- Expanding workforce with potential for career progression for top performers.
Software Engineer in Cambridge employer: Mackin Talent
Contact Detail:
Mackin Talent Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Software Engineer in Cambridge
✨Tip Number 1
Network like a pro! Reach out to folks in your field on LinkedIn or at local meetups. 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 tooling. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by practising common technical questions and coding challenges. Use platforms like LeetCode or HackerRank to sharpen your skills and boost your confidence before the big day.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented software engineers, and applying directly can sometimes give you an edge. Plus, it’s super easy!
We think you need these skills to ace Software Engineer in Cambridge
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Software Engineer role. Highlight your experience with Python, deep learning frameworks like PyTorch or TensorFlow, and any work with distributed infrastructure. We want to see how your skills match what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about the role and how your background makes you a great fit. Don’t forget to mention your experience with ML tooling and collaboration with research teams.
Showcase Your Projects: If you've worked on relevant projects, make sure to include them! Whether it's a personal project or something from your previous job, we love seeing practical examples of your skills in action, especially those involving complex data sets or ML systems.
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to keep track of your application status. Plus, we love seeing candidates who take that extra step!
How to prepare for a job interview at Mackin Talent
✨Know Your Tech Inside Out
Make sure you’re well-versed in Python and the deep learning frameworks mentioned, 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 write clean, maintainable code and your experience with large data sets for machine learning.
✨Emphasise Collaboration
Since teamwork is key, think of instances where you’ve worked closely with researchers or cross-functional teams. Be ready to discuss how you gather requirements and develop solutions that meet user needs, showcasing your communication skills.
✨Stay Curious and Adaptable
Demonstrate your eagerness to learn and adapt to new technologies. Share experiences where you’ve embraced ambiguity in problem-solving, especially in AR/VR contexts, to show that you can thrive in a dynamic environment.
