Machine Learning Engineer

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!

About Connect
Adobe Connect, within Adobe DALP BU is one of the best online webinar and training delivery platform. The product has a huge customer base which has been using it for many years. The product has evolved magnificently over a period of time ensuring it stay on top of the latest tech stack. It offers opportunity to look at plethora of technologies on both client and server side.
What You’ll Do:
· Hands-on Machine Learning Engineer who will release models in production.
· Develop classifiers, predictive models, and multi-variate optimization algorithms on large-scale datasets using advanced statistical modeling, machine learning, and data mining.
· Special focus on R&D that will be building predictive models for conversion optimization, Bidding algorithms for pacing & optimization, Reinforcement learning problems, 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.
· Responsible for driving all aspects of ML product development: ML modeling, data/ML pipelines, quality evaluations, productization, and ML Ops.
· Create and instill a team culture 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 require:
· Solid foundation in machine learning, classifiers, statistical modeling and multivariate optimization techniques
· Experience with control systems, reinforcement learning problems, and contextual bandit algos.
· Experience with DNN frameworks like TensorFlow or PyTorch on large-scale data sets.
· TensorFlow, R, scikit, pandas
· Proficient in one or more: Python, Java/Scala, SQL, Hive, Spark
· Good to have - Git, Docker, Kubernetes

. GenAI, RAG pipelines a must have technology

. Cloud based solutions is good to have
· 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:
· A total of 10+ years of experience, including at least 5 years in technical roles involving Data Science, Machine Learning, or Statistics.
· Masters or B.Tech in Computer Science/ Statistics
· 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.
· Demonstrated ability to influence technical and non-technical stakeholders.
· Proven ability to effectively manage 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 relentless pursuit of great customer experiences and continuous improvements to the product. ​

Adobe is proud to be an Equal Employment Opportunity employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other applicable characteristics protected by law. Learn more.

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