At a Glance
- Tasks: Join our Trust & Safety team to develop cutting-edge computer vision models for a safer Bumble experience.
- Company: Bumble Inc., a leader in building healthy relationships through innovative tech.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on innovation and personal development.
- Why this job: Make a real impact on user safety while working with the latest machine learning technologies.
- Qualifications: Advanced degree in Computer Science or related field, with strong ML and computer vision experience.
The predicted salary is between 70000 - 90000 £ per year.
Bumble is looking for a Senior Machine Learning Engineer (Computer Vision) to join our Trust & Safety team and play a key role fulfilling our mission to create a world where all relationships are healthy and equitable. We are looking for talents with a deep understanding of computer vision algorithms and rich hands-on experience in building vision systems. This means exploring, developing and deploying state-of-the-art machine learning models that help Bumble provide a safe and engaging experience for our users and improve the way Bumble operates.
With millions of images and messages exchanged on our platform every day, there is a wealth of opportunity to make a real difference in this role and help people to find love all over the world! The ideal candidate combines strong business acumen, extensive experience in machine learning applications (specifically in Computer Vision) along with a passion for tech.
WHAT YOU WILL BE DOING
- Work in a cross-functional team alongside data scientists, machine learning engineers, engineering and product teams.
- Explore, develop and deliver new cutting-edge technologies for computer vision/machine learning applications like image classification, facial recognition and synthetic image generation.
- Participate in cutting-edge research in computer vision.
- Set up and conduct large-scale experiments to test hypotheses and drive product development.
- Implement state-of-the-art machine learning models for measurable impact across the business.
- Partner with business functions and engineering teams to help frame problems into scalable AI solutions and solve key problems by leveraging the large and complex datasets at our disposal.
- Keep up with state-of-the-art research with the opportunity to create prototypes for the business and publish at top conferences.
WE’D LOVE TO MEET SOMEONE WITH
- An advanced degree in Computer Science, Mathematics or a similar quantitative discipline - a Ph.D. is a bonus.
- Proven experience in ML with a Computer Vision focus.
- Experience in designing, developing, and training ML models for large-scale deployments.
- Experience in leading ML projects in the industry, from gathering requirements with stakeholders to production roll out and monitoring.
- Experience in training and benchmarking dataset creation from dataset scoping, definition, preparation, and pre-processing for ML training.
- Understanding of software development life cycle processes and tools - ETL pipelines, CI/CD, MLOps, agile methodologies, version control (git), testing frameworks.
- Experience accessing and combining data from multiple sources and building data pipelines.
- Strong statistical modelling background - hypotheses testing, inference, regressions, random variables.
- Ability to work collaboratively and proactively in a fast-paced environment alongside scientists, engineers and non-technical stakeholders.
- Ability to combine business intuition with the application of advanced solutions.
- A passion for keeping up with the latest ongoings in Data Science and Machine Learning communities.
- A curious mind, self-starter and endlessly keen to learn and develop themselves professionally.
AN ADDED BONUS IF YOU HAVE
- An understanding of/experience with the Trust & Safety space.
- Experience with cloud infrastructures - GCP is a plus.
- Publications in top data science conferences like KDD, ECML, NeurIPS.
Senior Machine Learning Engineer (Computer Vision) - Trust & Safety employer: Bumble
Bumble is an exceptional employer that fosters a collaborative and innovative work culture, where employees are empowered to make a meaningful impact on the safety and engagement of millions of users worldwide. With a strong focus on professional growth, Bumble offers opportunities for continuous learning and development in cutting-edge technologies, particularly in the field of machine learning and computer vision. Located in a vibrant tech hub, employees benefit from a dynamic environment that encourages creativity and teamwork, making it an ideal place for those passionate about technology and social impact.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Machine Learning Engineer (Computer Vision) - Trust & Safety
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Bumble or similar companies. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those related to computer vision. This is your chance to demonstrate your hands-on experience and passion for tech.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss your past projects and how they relate to the role at Bumble. Practice makes perfect!
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're genuinely interested in joining the Bumble team.
We think you need these skills to ace Senior Machine Learning Engineer (Computer Vision) - Trust & Safety
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Senior Machine Learning Engineer role. Highlight your experience with computer vision algorithms and any relevant projects you've worked on. We want to see how your skills align with what Bumble is 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 Trust & Safety space and how your background makes you a perfect fit for the team. Let us know what excites you about working at Bumble!
Showcase Your Projects:If you've got hands-on experience with machine learning models, don't hold back! Include links to your GitHub or any publications that showcase your work in computer vision. We love seeing real-world applications of your skills!
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 the initiative to connect directly with us!
How to prepare for a job interview at Bumble
✨Know Your Algorithms
Make sure you brush up on your computer vision algorithms before the interview. Be ready to discuss how you've applied these in real-world scenarios, especially in image classification and facial recognition. Bumble is looking for someone who can not only talk the talk but also walk the walk!
✨Showcase Your Projects
Prepare to share specific examples of machine learning projects you've led or contributed to. Highlight your role in gathering requirements, developing models, and deploying them at scale. This will demonstrate your hands-on experience and ability to drive measurable impact.
✨Understand the Business Context
Bumble values candidates who can combine technical skills with business acumen. Think about how your work in machine learning can solve key problems for the company and improve user safety. Be ready to discuss how you would frame technical challenges into scalable AI solutions.
✨Stay Current and Curious
Show your passion for the field by discussing recent advancements in machine learning and computer vision. Mention any relevant publications or conferences you've attended. This will reflect your commitment to continuous learning and staying ahead in the tech landscape.
