Full Job Description
Adobe Firefly's Applied Science & Machine Learning (ASML) group is looking for research scientists and engineers focused on post-training, alignment, and distillation of large-scale generative AI models. Our goal is to push the frontier of generative AI while ensuring models are safe, efficient, aligned with user intent, and deployable at scale.
We are particularly interested in candidates with expertise in reinforcement learning from human feedback (RLHF), direct preference optimization (DPO/GRPO), supervised fine-tuning (SFT), and model distillation / efficiency methods. This work directly impacts the quality, efficiency, and safety of Firefly's image and video generation models, enabling next-generation creative workflows for millions of users.
As an Applied Scientist at Adobe, you will join a world-class team of applied researchers and engineers building the future of digital experiences. You will have the opportunity to innovate across the full post-training stack, collaborate across data, modeling, and product, and see your work ship to customers worldwide.
Job Responsibilities
37 Conduct innovative research and development in post-training alignment and model distillation for large-scale generative AI models.
37 Design and evaluate techniques such as RLHF, DPO/GRPO, SFT, reward modeling, and preference optimization to improve instruction-following, controllability, and safety.
37 Develop efficient distillation, compression, and inference acceleration methods to make frontier models deployable at scale.
37 Collaborate with researchers, engineers, and product teams to transfer post-training innovations into Adobe products.
37 Build and maintain pipelines to evaluate generative models across quality, efficiency, and safety metrics.
37 Convert research ideas/papers into production-ready implementations in Python and modern ML toolkits.
37 Provide technical mentorship and guidance to peers and junior researchers.
What you'll need to succeed
37 Master's or Ph.D. in Computer Science, Machine Learning, or a related field.
37 Strong hands-on experience with large-scale generative AI training and post-training (SFT, RLHF, DPO/GRPO, distillation).
37 Familiarity with diffusion models, transformers, or other state-of-the-art generative architectures.
37 Excellent communication skills and ability to collaborate across cross-functional teams.
37 Strong coding and prototyping ability in Python, PyTorch, and ML infrastructure tools.
37 Working with product teams on technology transfers
37 Good publication record in Computer Science, AI/ML or related fields
#FireflyGenAI
Expected Pay Range:
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 $142,700 -- $270,950 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 Washington, the pay range for this position is $168,600 - $244,200
At Adobe, for sales roles starting salaries are expressed as total target compensation (TTC = base + commission), and short-term incentives are in the form of sales commission plans. Non-sales roles starting salaries are expressed as base salary and short-term incentives are in the form of the Annual Incentive Plan (AIP).
In addition, certain roles may be eligible for long-term incentives in the form of a new hire equity award.
