Adobe Firefly's
Generative AI Services team is seeking a
Machine Learning Engineer for our GenAI Services area. In this high-impact role, you will work with a team of talented engineers in building scalable, high-performance generative AI systems-powering features across Adobe products like Firefly, Photoshop, Illustrator, Express, Stock, and Premiere. You will design and develop efficient inference pipelines, optimize models for latency and through at inference, and build APIs and ecosystems that integrate both Adobe's first-party and third-party generative models into Adobe suite of products that serve individual and enterprise customers. You will tackle Adobe's most complex engineering challenges at the forefront of the industry and help set technical direction while collaborating with other ML engineers.
By using statistical and econometric methods, predictive models, experimental design methods, and optimization techniques, the candidate will be working on the research and development of exciting projects like attribution, media mix modeling, budget optimization, personalization, causal analysis, time series analysis.
Ideal candidates will have a strong academic background as well as technical skills including applied statistics, machine learning, data mining, and software development. Familiarity with working with large-scale datasets and big data techniques would be a plus.
What You'll Do- Core GenAI Services Development: Design and develop APIs and services that integrate a wide range of generative models into Adobe's flagship products, ensuring seamless user experiences.
- ML Pipeline Optimization: Build and optimize GPU-accelerated pipelines for model training and inference, prioritizing performance, scalability, and reliability across enterprise-scale deployments.
- Model Integration & Productization: Collaborate with Adobe Research and model developer teams to implement inference strategies and productionize modern generative models.
- Enterprise-Scale Systems: Design and build ML workflows for enterprise-scale model customization, serving, and ecosystem integration that handle massive user loads.
- Technical Excellence: Foster an atmosphere of creativity and technical expertise while addressing Adobe's groundbreaking engineering challenges.
- Develop predictive models on large-scale datasets to address various business problems with advanced statistical modeling, machine learning, and analytics techniques.
- Develop and implement scalable and efficient modeling algorithms that can work with large-scale data in production systems
- Collaborate with product management and engineering groups to develop new products and features.
What You Need to Succeed- PhD or MS degree in Computer Science, Statistics, Electrical Engineering, Applied Math, Operations Research, Econometrics or equivalent experience required
- 0-2+ years of experience in specific skill/field(s)
- Deep understanding of statistical modeling, machine learning, deep learning, or data mining concepts, and a track record of solving problems with these methods.
- Proficient in one or more programming languages such as Python, Scala, Java and C
- Familiar with one or more machine learning or statistical modeling tools such as R, Matlab and scikit learn
- Knowledge and experience of working with relational databases and SQL
- Strong analytical and quantitative problem-solving ability.
- Outstanding communication and relationship skills, and a great teammate.
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 $125,600 -- $234,150 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 $142,500 - $206,275
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.
