ML Software Engineer Jobs at Adobe with Visa Sponsorship
ML Software Engineer jobs at Adobe involve applied research, large-scale model deployment, and deep integration with creative product pipelines. The company has a consistent record of sponsoring work visas across multiple categories for engineering talent, making it a realistic target if you're navigating the U.S. immigration process.
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The Opportunity
Firefly Foundry is a new business venture at Adobe — an enterprise managed-service offering for custom multimedia generative AI. The offering includes deep-tuned custom image, video, and 3D models built on each customer’s IP, paired with creative workflows for content production and VFX, deployed across new and existing Adobe surfaces, and surrounded by a media intelligence layer. The business has gained significant traction in Media & Entertainment (M&E), marketing, and consumer retail, and is rapidly expanding into adjacent verticals. We are hiring a Director, ML Engineering to own the engineering function behind Firefly Foundry’s model services at enterprise scale. This is a multi-faceted executive role with end-to-end accountability for how Firefly Foundry’s models are productionized, served, and operated for our enterprise customers — and for the engineering organization that delivers that capability.
What This Role Owns
You will define and implement the technical strategy that turns Firefly Foundry from a managed service for early-design partners into a platform capable of serving hundreds of enterprise customers concurrently — each with their own IP, tenancy boundaries, and SLAs — powering everything from franchise extensions and new IP development to modern GenAI workflows at production scale. Specifically, you will:
- Set the engineering operating model for productionizing custom generative models across image, video, and 3D — including the architectural patterns that simplify pipeline construction and let us absorb a heterogeneous mix of internal and external models without linear engineering cost.
- Own the unit economics of Firefly Foundry inference. Cost-to-serve, GPU utilization, and gross margin on the managed service are your numbers.
- Define the tenancy and data-isolation architecture that lets us honor enterprise IP contracts under audit.
- Drive the self-serve roadmap that broadens Firefly Foundry’s reach and value beyond hands-on engagements.
- Represent Adobe engineering in C-suite and senior technical conversations with studios, brands, and global enterprises — including VPs of Production, CTOs, and Chief Digital Officers.
Who You Will Partner With
- Applied Science — to ensure inference quality matches the training environment, and to make prioritization calls on emerging techniques for multimedia
- Firefly Foundry Studio — to translate ambitious creative visions into reliable, high-performance ML systems that transform how content is conceived, produced, and delivered, and into concrete roadmaps with clear milestones and success metrics.
- Post-sales field organization — engagement managers and creative technologists in customer engagements, where you serve as the engineering leadership representative and educate the field on APIs and services.
- AI Platform, and adjacent Adobe orgs — to negotiate shared infrastructure, accelerator capacity, and serving primitives at platform scale.
- Strategic partners — including GPU vendors and hyperscalers, where capacity planning, roadmap alignment, and partnership economics are part of your remit.
What You Will Do
Build and lead the engineering organization
- Lead a multi-team engineering organization of ML engineers and engineering managers; recruit, hire, develop, and retain senior technical and leadership talent, and build a culture of engineering rigor and delivery discipline.
- Hiring at scale is a material part of this role — Firefly Foundry is growing rapidly, and sustaining scaling momentum depends on it. You will integrate top technical and leadership talent into the organization at the pace the business demands.
- Establish the engineering bar, the bench, and the talent strategy that let Firefly Foundry sustain 10x growth in capability breadth and traffic without linear headcount growth.
- Define the operating rhythm — goal-setting, exec reviews, and engineering reviews — that keeps a fast-scaling org coordinated.
Define and own the technical strategy
- Own the multi-year architecture for training and inference at scale: pipeline construction, data pipelines, evaluation frameworks, model lifecycle management, and accelerator utilization (CUDA, NCCL, and the wider GPU stack).
- Set the strategy for fast model deployment, parallel pipeline operation at scale, tenancy/data isolation, and self-serve capability buildout.
- Make the build-vs-buy and prioritization calls on emerging GenAI techniques in partnership with Applied Science, based on material improvements in capability, cost, or speed.
Own production reliability and economics
- Hold the line on production SLAs for orchestrated and deployed model services.
- Own analytics and observability across every model pipeline — quality, latency, cost, and utilization.
- Drive cost-to-serve down on a multi-year curve while expanding capability.
Drive customer and partner outcomes
- Represent engineering in technical customer engagements with enterprise customers — translating creative and business requirements into ML roadmaps, milestones, and success metrics.
- Co-design scalable, cost-efficient serving for real-time on-set use cases and high-volume social content generation, in partnership with infrastructure and platform teams.
- Steward the GPU vendor and hyperscaler relationships that underwrite Firefly Foundry’s serving capacity.
What You Bring
Leadership scope
- 10+ years in applied machine learning and ML systems, including 5+ years leading engineering organizations — with prior experience leading managers of managers.
- Demonstrated success shipping generative AI products in production at enterprise scale.
- Proven ability to operate as a peer to VP-level partners across product, science, infrastructure, and field organizations, and to represent engineering credibly in front of senior customer and partner executives.
- Track record of building engineering benches, defining career frameworks for emerging roles, and developing leaders who themselves become directors.
Technical judgment
- Deep understanding of the modern generative model landscape (diffusion, transformers, VAEs, latent video models, control/adapters, or similar) — enough to make architecture, investment, and prioritization calls with confidence, in close partnership with Applied Science.
- Strong intuition for the economics and engineering reality of large-scale inference: accelerator stacks, model optimization and quantization, and the tradeoffs between quality, latency, and cost.
- Experience designing and operating ML systems end-to-end — data, training, evaluation, deployment, monitoring, and continuous improvement — at production scale.
- Familiarity with high-resolution media pipelines (4K+ video, high bit-depth) or adjacent bandwidth- and latency-sensitive domains is a meaningful plus.
Communication and judgment
- Executive presence and communication skills — able to brief executives, customers, and partners credibly, and to work directly with creative, production, and business collaborators to turn ambiguous problems into clear technical plans.
- Sound judgment under ambiguity — comfortable making decisions with incomplete information and revising as new information arrives.
Education
- MS or PhD in Computer Science, Electrical Engineering, or a related field, or equivalent practical experience building and leading advanced ML systems.
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 accommodations@adobe.com 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.
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 $206,400 -- $384,675 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 $265,700 - $384,675. 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.
State-Specific Notices:
California: Fair Chance Ordinances Adobe will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and “fair chance” ordinances.
Colorado: Application Window Notice If this role is open to hiring in Colorado (as listed on the job posting), the application window will remain open until at least the date and time stated above in Pacific Time, in compliance with Colorado pay transparency regulations. If this role does not have Colorado listed as a hiring location, no specific application window applies, and the posting may close at any time based on hiring needs.
Massachusetts: Massachusetts Legal Notice It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
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Get Access To All JobsTips for Finding ML Software Engineer Jobs at Adobe
Align your portfolio to Adobe's ML stack
Adobe's ML roles emphasize generative AI, computer vision, and large language models tied to creative tools like Firefly. Tailor your GitHub projects and research papers to show applied work in these areas before applying.
Verify your visa type matches the role level
Adobe sponsors H-1B, E-3, TN, and F-1 OPT across engineering levels, but the right category depends on your citizenship and degree. Confirm your eligibility before the recruiter screen so you can answer sponsorship questions without hesitation.
Start OPT paperwork before your campus interview
If you're on F-1 status, your DSO needs lead time to authorize OPT. USCIS recommends filing up to 90 days before your program end date. Delays here can push your start date past what Adobe's offer timeline allows.
Target teams shipping production ML systems
Adobe's Sensei and Firefly teams actively hire ML engineers to ship features at scale, not just prototype. Roles in these orgs are more likely to move quickly through internal headcount approval, which keeps the offer-to-filing window predictable.
Clarify LCA timing during the offer stage
Your employer must file a certified Labor Condition Application with DOL before USCIS can process your H-1B petition. Ask Adobe's immigration team when LCA filing begins after signing your offer so you can plan your start date accurately.
Use Migrate Mate to find open ML roles at Adobe
Adobe posts ML Software Engineer openings across experience levels and product areas. Use Migrate Mate to filter for Adobe roles that explicitly support visa sponsorship, so you're applying to positions already confirmed for international candidates.
Frequently Asked Questions
Does Adobe sponsor H-1B visas for ML Software Engineers?
Yes, Adobe sponsors H-1B visas for ML Software Engineers. The company works with immigration counsel to file H-1B petitions on behalf of selected candidates, covering the Labor Condition Application through USCIS approval. Because H-1B is subject to an annual lottery, timing your application to the April registration window is essential if you're not already H-1B exempt.
How do I apply for ML Software Engineer jobs at Adobe?
Apply directly through Adobe's careers site or find open ML Software Engineer roles filtered by sponsorship eligibility on Migrate Mate. Most ML roles at Adobe include a recruiter screen, a technical phone interview focused on ML fundamentals and system design, and a virtual onsite covering coding, modeling, and cross-functional communication. Having your visa status and intended start date ready early keeps the process moving.
Which visa types does Adobe commonly use for ML Software Engineers?
Adobe sponsors H-1B for most international ML engineers, along with E-3 visa for Australian citizens, TN visa for Canadian and Mexican nationals in qualifying roles, and F-1 OPT or CPT for students in eligible programs. For longer-term pathways, Adobe supports EB-2 and EB-3 Green Card sponsorship for engineers who meet the experience thresholds after establishing tenure.
What qualifications does Adobe expect for ML Software Engineer roles?
Most Adobe ML Software Engineer postings require a bachelor's degree or higher in computer science, electrical engineering, or a closely related field. Practical experience with deep learning frameworks like PyTorch or TensorFlow, familiarity with large-scale model training, and demonstrated ability to ship ML features in production environments carry significant weight during the technical evaluation.
How do I time my application if my OPT or visa status is expiring soon?
If your F-1 OPT is expiring, Adobe's offer timeline needs to align with your USCIS-authorized work period. STEM OPT extensions give you up to 24 additional months, but your employer must be enrolled in E-Verify. For H-1B transfers from another employer, Adobe can file a cap-exempt petition and you can begin work once USCIS confirms receipt, without waiting for full approval.