Machine Learning Engineer 5

About the Role We are looking for a Senior Machine Learning Engineer with deep
expertise in generative modeling and computer vision to join Adobe's Applied AI
team. In this role, you will architect and ship state-of-the-art diffusion-based
models, drive applied research into production, and mentor a team of talented
engineers. You will work at the intersection of cutting-edge research and
real-world impact — translating the latest advances in generative AI into
scalable, reliable systems. Key Responsibilities Generative Modeling Design,
train, and fine-tune large-scale diffusion models (DDPM, DDIM, LDM, DiT) for
image, video, and multimodal generation tasks. Drive improvements in sampling
efficiency — distillation, consistency models, progressive training, and guided
generation techniques. Stay current with and rapidly prototype ideas emerging
from the broader AI community. Computer Vision & Perception Build
production-grade pipelines for image/video understanding: segmentation,
detection, depth estimation, optical flow, and 3D reconstruction. Develop and
fine-tune vision foundation models (ViT, CLIP, DINOv2, SAM) for downstream tasks
using parameter-efficient methods (LoRA, adapters). Integrate vision encoders
with generative backbones for controllable generation (ControlNet, IP-Adapter,
inpainting, editing). Applied ML & Systems Own the full ML lifecycle: data
curation, experiment tracking, model evaluation, optimization, deployment, and
monitoring. Optimize models for inference: quantization (INT8/FP8), ONNX export,
Flash Attention, and xFormers. Design scalable training infrastructure on
distributed GPU clusters (DDP, FSDP, DeepSpeed) across thousands of GPU-hours.
Define and instrument evaluation frameworks, benchmarks, and human preference
studies (RLHF / DPO) to measure generative quality. Leadership & Collaboration
Lead technical design reviews, write engineering RFCs, and set quality standards
for the team. Mentor junior and mid-level ML engineers through code reviews,
1:1s, and pair-programming sessions. Collaborate with product, research, and
infrastructure teams to translate research ideas into shipped features. Required
Qualifications 10 - 14 years of hands-on ML engineering experience in industry
or research. MS or PhD in Computer Science, Machine Learning, Statistics, or
equivalent practical experience. Expert-level Python; strong, mandatory
proficiency in PyTorch. Deep theoretical and practical knowledge of score-based
and diffusion models. Strong background in computer vision fundamentals: CNNs,
ViTs, feature pyramids, multi-scale processing. Experience fine-tuning large
vision and generative models at scale. Proficiency with distributed training
frameworks (DDP, FSDP, DeepSpeed, Megatron-LM). Solid grasp of probabilistic ML,
variational inference, and information theory. Experience with MLOps tooling
(Weights & Biases, MLflow, DVC, or equivalent). Track record of shipping ML
models to production at scale. Excellent written and verbal communication skills
with cross-functional stakeholders. Preferred Qualifications Experience with
flow-based generative models (normalizing flows, CNFs, Rectified Flow, Flow
Matching). Experience with video generation models (Sora-style architectures,
CogVideo, AnimateDiff, SVD). Familiarity with 3D generative models (NeRF, 3D
Gaussian Splatting, Zero-1-to-3, Point-E). Background in multimodal systems
(LLMs + vision: GPT-4V, LLaVA, InstructBLIP-style architectures). Experience
with RLHF / DPO for generative model alignment and preference optimization.
Active open-source contributions — maintained repos, significant PRs to projects
like HuggingFace Diffusers, CompVis, timm, or similar. Active GitHub presence
demonstrating ongoing engagement with the ML community. Equal Opportunity
Statement Adobe is an equal opportunity employer. We celebrate diversity and are
committed to building an inclusive environment for all employees. We do not
discriminate on the basis of race, religion, color, national origin, gender,
sexual orientation, age, marital status, veteran status, or disability status.
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sexual orientation, gender identity or expression, veteran status, or any other
applicable characteristics protected by law. Learn more. Adobe aims to make
Adobe.com 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 accommodations@adobe.com or call (408) 536-3015.