Senior Machine Learning Infrastructure Engineer
Seattle, WA, USA
This job was posted on:
$80 - 95k
Changing the world through digital experiences is what Adobe’s all about. We give everyone—from emerging artists to global brands—everything they need to design and deliver exceptional digital experiences. We’re passionate about empowering people to craft alluring and powerful images, videos, and apps, and transform how companies interact with customers across every screen.
Passionate about creating new products and prototypes that harness the power of machine learning? This is your opportunity to join an extraordinary team of researchers, engineers, and software developers who are inventing the next generation of creative tools powered by machine learning. Adobe Research is looking for an outstanding Machine Learning Infrastructure Engineer to help us dramatically accelerate our prototyping and experimentation processes.
What You'll Do
- Collaborate with a multi-disciplinary team of extraordinary engineers and researchers to build the next generation of creative tools. This is a “best of both worlds” opportunity where you’ll have the flexibility, scope, and personal impact of joining a startup, but also the deep resources, cool perks, and global launch stage that only an industry leader like Adobe can offer.
- Be responsible for proposing, design, and implementing new pieces of infrastructure that make our machine learning investigations faster, more affordable, and more flexible.
- Create the tools that help your team better understand how our algorithms are performing, and that assist us in crucial tasks like understanding and reducing cultural bias inherent in data.
- Advocate for adoption of new technologies and standards to the broader Adobe developer community.
- Research and build standard methodologies and share them with the organization.
- Mentor & coach junior technical contributors.
What You Need to Succeed
- B.S., M.S., or Ph.D. in Computer Science, Electrical Engineering, Applied Mathematics, or related technical fields.
- 5+ years of relevant industry experience, including experience collaborating with machine learning researchers and engineers.
- Experience designing systems for structured data storage, including experience with popular databases (e.g., MongoDB, PostgreSQL) and cloud data solutions (e.g., CosmosDB, DynamoDB).
- Experience with scaling computation in the cloud, including experience with distributed systems tooling such as Kubernetes, and with cloud compute platforms such as Azure AKS and Amazon EC2/EKS.
- Working knowledge of machine learning libraries commonly used for training and inference (e.g. TensorFlow, PyTorch).
- Working knowledge of data management best practices, including technical approaches for handling privacy-sensitive data, and data which requires regulatory compliance.
- A combination of critical thinking and pragmatic delivery to yield the best short-term as well as long-term results. Passionate about product excellence.
- Ability to influence & direct multi-functional teams without formal authority. Inherently collaborative, while also demonstrating leadership to successfully implement a sophisticated product or technical roadmap.
- Ability to effectively and convincingly communicate ideas and objectives to audiences of all levels.
- Experience with frontend web technologies such as React.
- Experience with, or interest in, video creation and live streaming.