Machine Learning Engineer

Our Company

Adobe – Changing the world through digital experiences. We empower everyone—from emerging artists to global brands—to design and deliver exceptional digital experiences. We are committed to equal opportunity and fostering an environment where new ideas can come from anywhere in the organization.

We are seeking a highly experienced and innovative Staff Machine Learning Engineer to join the Gen Studio Engineering team. This role is ideal for a technical leader who thrives in a fast-paced environment and is passionate about building scalable, high-impact software solutions. You will drive architectural decisions, mentor engineers, and influence the technical direction of Gen Studio.

• Design, build, test, and maintain AI/ML-based systems and applications that serve as the backbone of scalable, production-ready technology stacks.
• Frame product features as ML tasks (e.g., classification, recommendation, context engineering).
• Analyze trade-offs across cost, latency, and accuracy while ensuring compliance with UX, privacy, legal, and security constraints.
• Assess data distribution (variance, sampling, drift) and manage data labeling workflows involving LLMs, SMEs, or user-generated activity.
• Organize datasets for training, validation, and testing, and engineer high-quality features using normalization, smoothing, and weighting techniques.
• Implement and adapt techniques from academic research and industry papers; evaluate algorithmic trade-offs considering data requirements, latency, and runtime.
• Handle cold-start scenarios and mitigate overfitting/under fitting challenges.
• Define offline benchmarks and metrics; design and analyze A/B tests to validate online performance.
• Architect scalable ML systems (e.g., multi-agent, recommender, active learning, multi-stage model training, enterprise search) for offline and online workflows.
• Optimize model development and deployment in GPU/TPU environments using PyTorch.
• Work cross-functionally with data, research, and product teams to translate models into production-ready services.

• 12+ years of experience in software engineering with a strong track record of technical leadership.
• Bachelor’s or Master’s degree in Computer Science or a related field (or equivalent experience).
• Proven expertise in Machine Learning and Deep Learning, including model design, optimization, and fine-tuning.
• Strong understanding of transfer learning principles and their application in production settings.
• Proficiency in Python (especially for data workflows) and experience with ML/DL frameworks such as PyTorch, Tensor Flow/Keras, CUDA, Hugging Face, and JAX.
• Experience designing and deploying scalable AI/ML systems optimized for GPU/TPU environments.
• Solid grasp of data engineering concepts—including dataset management, feature engineering, and handling data drift.
• Ability to balance theoretical ML knowledge with practical, high-performance implementation.
• Strong understanding of how to transform models into reliable, production-grade services.

• Recognized as a thought leader within and beyond the organization.
• Experience mentoring senior engineers and shaping engineering culture.
• Demonstrated ability to drive innovation and evangelize new technologies.
• Experience with building GenAI-first applications.
• Contributions to industry forums, conferences, or open-source communities.

Our compensation reflects the cost of labor across several U.S. geographic markets, and we pay differently based on those defined markets. The U.S. pay range for this position is $172,500 -- $306,625 annually. Pay within this range varies by work location and may also depend on job-related knowledge, skills, and experience. Your recruiter can share more about the specific salary range for the job location during the hiring process.

In California, the pay range for this position is $211,800 - $306,625.

At Adobe, for sales roles starting salaries are expressed as total target compensation (TTC = base + commission). Non-sales roles starting salaries are expressed as base salary and short-term incentives in the form of the Annual Incentive Plan (AIP).

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