Applied Scientist (AI/ML/Computer Vision)
Getty is embarking on its next wave of innovation in visual storytelling and how to put the perfect image or video in our customer’s hands, be it for a society-changing headline or a brand’s next big campaign—truly moving the world with images.
We are looking for an Applied Scientist specializing in artificial intelligence, machine learning, and computer vision to join a new AI/ML Team. In this role, you’ll research, build, and deploy new models that understand Getty’s imagery to improve our customer’s search experience, be it for personalization, diversifying search results, enabling customer exploration and discovery, or image manipulation.
You’ll have access to a growing, rich dataset of the most trusted, esteemed, and diverse visual content in the world with over 250 million award-winning images and videos encompassing the latest global news coverage from red carpet events to football stadiums to conflict zones; exclusive conceptual creative images; and the world’s largest commercial archive. The metadata on our content is human-judged and curated by our creative researchers with unmatched expertise. With a global presence, our search interaction data comes from over 50 million unique visitors a quarter from almost every country in the world.
What you’ll be doing:
- Research, build, and validate machine learning models, leveraging our images, metadata, and customer interactions to understand our imagery and power new experiences. Some examples of projects may include building models for:
- Semantic understanding of our images and video
- Visual search
- Understanding customer intent
- Accelerating our creative researcher’s editing process (human-in-the-loop)
- Partner closely with other data scientists, product, engineering, user research, design, and/or creative image experts to build models aligned with customer needs and bring to production
- Collaborate closely with machine learning, product, and search leaders to help drive strategic directions and product roadmap
We’d love to hear from you if:
- Proven experience building computer vision models for customer-facing products.
- A strong understanding of the real-world advantages and drawbacks of various machine learning techniques in products.
- Hands-on experience with accessing data, Python, machine learning libraries, and deep learning libraries (ex: tensorflow, opencv, scikit-learn, numpy, pandas, scipy, SQL, hive, spark, ).
- You write clean, understandable code that follows best practices, is well-documented, and allows for easily reproducible models.
- You are excited to dig into the context in which data was generated to consider biases that may exist in the data, and make appropriate considerations in developing solutions.
- Excellent communication skills. You are a good listener open to many diverse voices and perspectives. You are transparent, trustworthy, and honest.
- Ability to independently execute on a project, from ideation to testing to delivery, and can pro-actively interact with other data scientists and engineers to access necessary resources or data.
- A Ph.D. or MS in Computer Science, Statistics, Data Science, Mathematics, Economics/Sconometrics, Sociology, Natural Sciences or any other equivalent quantitative field is preferred. If you are self-taught and believe you are a good fit for this role, or have significant work experience, we would love to hear from you as well.
Getty Images is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. Getty Images believes that diversity is critical to our success in moving the world with images and is committed to creating an inclusive, mutually respectful environment which celebrates diversity. We seek to hire on the basis of merit, competence, performance, and business needs.