Machine Learning Engineer - Adobe Connect

Position Overview

Adobe Connect, within Adobe DALP BU, is seeking a hands-on Machine Learning Engineer to release models into production. This role involves developing classifiers, predictive models, and multi-variate optimization algorithms on large-scale datasets using advanced statistical modeling, machine learning, and data mining techniques. A special focus will be on R&D for building predictive models for conversion optimization, bidding algorithms for pacing & optimization, reinforcement learning problems, and forecasting. The successful candidate will collaborate with Product Management to bring AI-based assistive experiences to life and will be responsible for driving all aspects of ML product development, including ML modeling, data/ML pipelines, quality evaluations, productization, and ML Ops.

Responsibilities

• Develop classifiers, predictive models, and multi-variate optimization algorithms on large-scale datasets.
• Conduct R&D focusing on predictive models for conversion optimization, bidding algorithms for pacing & optimization, reinforcement learning problems, and forecasting.
• Collaborate with Product Management to implement AI-based assistive experiences and inform the product roadmap.
• Drive all aspects of ML product development: ML modeling, data/ML pipelines, quality evaluations, productization, and ML Ops.
• Create and foster a team culture focused on sound scientific processes and customer engagement.
• Manage project scope and risks using data, analytics, and creative problem-solving.

Requirements

• Solid foundation in machine learning, classifiers, statistical modeling, and multivariate optimization techniques.
• Experience with control systems, reinforcement learning problems, and contextual bandit algorithms.
• Experience with DNN frameworks like TensorFlow or PyTorch on large-scale datasets.
• Proficiency with:
  • TensorFlow, R, scikit, pandas
  • Python, Java/Scala, SQL, Hive, Spark (one or more)
• Must-have technology: GenAI, RAG pipelines.
• Good-to-have: Git, Docker, Kubernetes, Cloud-based solutions.
• General understanding of data structures, algorithms, multi-threaded programming, and distributed computing concepts.
• Ability to be a self-starter and collaborate effectively with data scientists and software engineers to design, test, and build production-ready ML and optimization models and distributed algorithms.

Ideal Candidate Profile

• 10+ years of experience, with at least 5 years in technical roles involving Data Science, Machine Learning, or Statistics.
• Master's or B.Tech in Computer Science/Statistics.
• Comfort with ambiguity, adaptability to evolving priorities, and 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 with large customer bases.
• Strategic thinking ability, foresight, and capacity to create a long-term vision.
• Relentless pursuit of great customer experiences and continuous product improvement.

Company Information

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!

Employment Type

Full time

Location Type

• Information not provided

Salary

• Information not provided

Adobe is proud to be an Equal Employment Opportunity employer.