Machine Learning Engineer, Computer Vision

Full-time

Job Description

This job posting has expired and no longer accepting applications.

Bumble is looking for a Machine Learning Engineer (Computer Vision) to join our Trust & Safety team and play a key role in fulfilling our mission to create a world where all relationships are healthy and equitable. Concretely, 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.

Base Compensation Range: $135,000 - $188,000. For base compensation, we set standard ranges for all roles based on function, level, and geographic location. This position is also typically eligible to participate in our short- and long-term incentive programs. Benefits include Medical, Dental, Vision, 401(k) match, Unlimited Paid Time Off Policy.

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 deploying high-load ML applications on container orchestrators (K8s, Kubeflow, etc)

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

We strongly encourage people of colour, lesbian, gay, bisexual, transgender, queer and non-binary people, veterans, parents, and individuals with disabilities to apply. Bumble is an equal opportunity employer and welcomes everyone to our team. If you need reasonable adjustments at any point in the application or interview process, please let us know.

In your application, please feel free to note which pronouns you use (For example - she/her/hers, he/him/his, they/them/theirs, etc).

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