Sr. Machine Learning Engineer
Adobe, San Jose, 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!
Adobe Advertising is a combination of a ‘Demand Side Platform (DSP)’ and a ‘Spend Optimiser’ that helps customers plan, buy, measure, and optimize their digital media (across CTV, Online Video, Display, Search, Social, and Retail Media Networks). We solve hard problems involving very large data sets (400 billion auctions a day), low latency (20 ms response time for every auction), and AI / ML. We build product experiences that customers love for generating insights and taking action. We help the largest global advertisers improve the impact of their paid media budgets by delivering connected and personalized experiences to their consumers.
This is an in-office position in our San Jose, CA office.
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 conversion optimization, bidding algorithms for pacing & optimization, reinforcement learning, and forecasting.
- 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.
- Lead/Mentoring a diverse team of outstanding ML scientists and engineers while driving all aspects of ML product development: ML modeling, data/ML pipelines, quality evaluations, productization, and ML Ops.
- Build and instill a team that focuses on sound 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, and contextual bandit algorithms.
- 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 7+ 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 Real Time Bidding / Ad Tech background preferred.
- Comfort with ambiguity, adaptability to evolving priorities, and the ability to lead a team while working autonomously.
- Proven management experience with highly diverse and global teams.
- Proven track record to influence technical and non-technical stakeholders.
- Consistent track record of effectively operating in a high-growth, matrixed organization.
- Track record of delivering cloud-scale, data-driven products, and services that are widely adopted with large customer bases.
- 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.