Senior ML Engineer

Job title: Senior ML Engineer

About the Role Join Adobe's Firefly team within ASML as a Senior ML Engineer to advance multimodal generative AI for real-world creative products. You will start from foundational models, adapt them for diverse use cases, and build production-grade generation pipelines while collaborating with research, product, and infrastructure teams to push the boundaries of AI-powered creativity.

What You'll Do

• Foundational Model Development & Adaptation: Engage with large-scale pretrained models for multimodal generation (image, text, video, and beyond) and tailor them to support Adobe Firefly products and features.
• Research, prototype, and integrate brand-new techniques from the latest literature into production-grade generation pipelines.
• Construct and refine end-to-end pipelines for multimodal generation, balancing quality, performance, and scalability.
• Data Strategy & User Workflows: Work with data and research teams to review, modify, and recommend improvements to data strategies that support model training and fine-tuning. Analyze and iterate on user-facing workflows, translating product requirements into model and pipeline build decisions. Contribute to dataset curation, annotation strategy, and evaluation frameworks for generative models.
• Technical Excellence & Collaboration: Participate in build reviews and code reviews, uphold high standards for code quality, architecture, and reproducibility. Build and maintain robust technical documentation, design documents, and engineering standards. Collaborate with partner teams across ASML and contribute actively to technical roadmaps and cross-functional planning. Mentor junior engineers and share knowledge through pairing, code review, and internal technical talks.

What We're Looking For

• 5+ years of industry experience in machine learning engineering, with a strong focus on deep learning for computer vision or multimodal generation.
• Practical experience handling extensive, intricate ML codebases and current ML frameworks like PyTorch or TensorFlow in live settings.
• Demonstrated experience in constructing and refining ML pipelines on a large scale — covering model training and fine-tuning all the way through inference and deployment.
• Solid understanding of generative model architectures (e.g., diffusion models, transformers, GANs, VAEs) and experience adapting or training them for applied use cases.
• Strong Python proficiency and software engineering fundamentals, including system build, testing, and debugging.
• Experience in distributed training or inference on GPU clusters; knowledge of frameworks like Slurm or similar is an advantage.
• Extensive knowledge of multimodal generation workflows — especially image or video generation — and the capability to quickly adopt new methods from research.
• Demonstrated experience collaborating cross-functionally with research scientists, product managers, and infrastructure engineers.
• Ability to communicate technical trade-offs clearly and contribute meaningfully to roadmap discussions and architectural decisions.
• Comfort with ambiguity and the ability to thrive in a fast paced research and product environment.
• Experience contributing to technical documentation, development proposals, or engineering standards.
• Education: A Bachelor's degree in Computer Science, Machine Learning, Electrical Engineering, or a related field, or equivalent experience, is required. Master's degree or PhD, or equivalent experience, preferred.

Nice to Have

• Experience with controllable generation, LoRA / fine-tuning workflows, or RLHF-based alignment techniques.
• Familiarity with cloud platforms (AWS, Azure, or GCP) and MLOps tooling.
• Prior experience working in a creative AI or media technology domain.
• Contributions to open-source ML projects or peer-reviewed publications.

Compensation & Benefits Not specified in the posting.