Job Description
What You'll Do:
Develop classifiers, predictive models and multi variate optimization algorithms on
large-scale datasets using advanced statistical modeling, machine learning and data
mining.
Design, implement and operate scalable models that can work with large-scale datasets
(100s billions of records) in production systems.
Ability to articulate the design and implementation choices to cross functional teams
R&D will revolve around a few key focus areas such as Agentic AI solutions, predictive
models for conversion optimization, Reinforcement Learning, and Forecasting &
Planning.
Model Lifecycle Management: Manage model versioning, deployment strategies,
rollback mechanisms, and A/B testing frameworks. Coordinate model registries, artifacts,
and promotion workflows in collaboration with ML Engineers Develop CI/CD and
orchestration workflows using GitLab CI, GitHub Actions, CircleCI, Airflow, Argo
Workflows, or similar tools.
Review and optimize data science models, including code refactoring, containerization,
deployment, versioning, and performance tuning. Implement model testing, validation,
and automated QA pipelines, ensuring reproducibility and compliance.
Monitor models in production, including data drift, concept drift, performance
degradation, and system reliability.
Collaborate multi-functionally with data scientists, data engineers, and architects; build
documentation and improve team processes.
Ensure governance, security, and compliance for ML pipelines (access controls, audit
logs, model reproducibility, lineage).
What you require:
7-9 yrs. of relevant experience as ML engineer
Strong programming skills in Python, Java/Scala, SQL, Hive, Spark
Experience working on production systems involving machine learning, NLP, classifiers,
statistical modeling and multivariate optimization techniques, GenAI/LLM/Agentic
solutions.
Hands-on experience with MLOps frameworks like MLflow, Kubeflow, Airflow or
similar.
Experience with control systems, reinforcement learning problems, contextual bandit
algos
Experience with common ML libraries such as scikit-learn, TensorFlow, Keras, PyTorch.
Experience with software engineering guidelines including version control, testing, and
automation.
Experience with observability tools (Prometheus, Grafana, ELK, CloudWatch, Datadog)
Knowledge of cloud services such as AWS Sagemaker, Azure ML, GCP Vertex AI.
Knowledge of Docker, Kubernetes (EKS/GKE/AKS), and enterprise platforms like
OpenShift.
Familiarity with infrastructure-as-code (Terraform, CloudFormation)
Strong ability to design and implement cloud architectures for end-to-end ML workflows
on AWS.
Ability to understand data science workflows, experiment tracking, and feature
engineering tools.
Strong communication skills; ability to work collaboratively in multi-functional teams &
articulate the design and implementation choices to cross functional teams.
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
Strong analytical, quantitative problem solving, and communication skills
Proven ability to work well in a high performing team with agile development
approaches and technolog
About Adobe
Adobe empowers everyone to create through innovative platforms and tools that unleash creativity, productivity and personalized customer experiences. Adobe's industry-leading offerings including Adobe Acrobat Studio, Adobe Express, Adobe Firefly, Creative Cloud, Adobe Experience Platform, Adobe Experience Manager, and GenStudio enable people and businesses to turn ideas into impact, powered by AI and driven by human ingenuity.
Our 30,000+ employees worldwide are creating the future and raising the bar as we drive the next decade of growth. We're on a mission to hire the very best and believe in creating a company culture where all employees are empowered to make an impact. At Adobe, we believe that great ideas can come from anywhere in the organization. The next big idea could be yours.
Let's Adobe together
At Adobe, we believe in creating a company culture where all employees are empowered to make an impact. Learn more about Adobe life, including our values and culture, focus on people, purpose and community, Adobe for All, comprehensive benefits programs, the stories we tell, the customers we serve, and how you can help us advance our mission of empowering everyone to create.
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 protected characteristic. Learn more.
Adobe aims to make our Careers website and recruiting process accessible to any and all users. If you have a disability or special need that requires accommodation to navigate our website or complete the application process, email [Confidential Information] or call +1 408-536-3015.
AI Use Guidelines for Interviews:
Our interviews are designed to reflect your own skills and thinking. The use of AI or recording tools during live interviews is not permitted unless explicitly invited by the interviewer or approved in advance as part of a reasonable accommodation. If these tools are used inappropriately or in a way that misrepresents your work, your application may not move forward in the process.
At Adobe, we empower employees to innovate with AI and we look for candidates eager to do the same. As part of the hiring experience, we provide clear guidance on where AI is encouraged during the process and where it's restricted during live interviews. See how we think about AI in the hiring experience.
