Sr. Machine Learning Engineer
Adobe, San Francisco, CA, United States
Our Company
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 create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen.
We’re on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours!
Job level
P40
EMPLOYEE ROLE
Individual Contributor
Adobe is AI. We're building the worlds most sophisticated generative tools. We're not just building the tools, we're committed to doing it while supporting artists. We need to ensure that we're only training with ethically sourced content that pays the creator.
To build these tools we need data to train with. We need you to help build the tooling to enable it at scale.
What You’ll Do:
- Hands-on data scientist who will release models in production.
- Develop classifiers, predictive models, and multi-variate optimization algorithms on large-scale datasets using sophisticated statistical modeling, machine learning, and data analytics.
- Special focus on R&D that will be building predictive models for media intelligence.
- Collaborate with Product Management to bring AI-based Assistive experiences to life. Socialize what’s possible now or in the near future to inform the roadmap.
- Join team driving all aspects of ML product development: ML modeling, data/ML pipelines, quality evaluations, productization, and ML Ops.
- Champion scientific processes and encourages deep engagement with our customers.
- Handle project scope and risks with data, analytics, and creative problem-solving.
What you will need:
- Solid foundation in machine learning, classifiers, statistical modeling and multivariate optimization techniques.
- Experience with control systems, reinforcement learning problems.
- Proven experience with DNN frameworks like TensorFlow or PyTorch on large-scale production grade ML solutions.
- Proficient in one or more: Python, Java/Scala, SQL, Hive, Spark.
- Good to have - Git, Bazel, Docker, Kubernetes.
- General understanding of data structures, algorithms, multi-threaded programming, and distributed computing concepts.
- Ability to be a self-starter and work closely with other data scientists and software engineers to design, test, and build production-ready ML and optimization models and distributed algorithms running on large-scale data sets.
Ideal Candidate Profile:
- Demonstrated ability, with 5+ years of experience, in hands on technical roles involving Data Science, Machine Learning, or Statistics.
- PhD or MS Eng in Computer Science / Statistics / equivalent field.
- Experience with Computer Vision.
- Comfort with ambiguity, adaptability to evolving priorities, and the ability to lead investigations while working autonomously.
- An ability to think strategically, look around corners, and create a vision for the current quarter, the year, and five years down the road.
- A self-motivated and can-do attitude in the pursuit of great customer experiences and continuous improvements to the product.