Noida, Uttar Pradesh, India
Likely evergreen, first seen by us 79 days agoEmployment type in the employer’s posting: Full timeFrom the employer’s posting
Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team.
In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users.
Build and train deep learning models from scratch, including custom transformers
Own the full training stack, from event tokenization through fine-tuning
Train large models on GPUs using mixed precision and distributed strategies
Build feature pipelines on Databricks and Spark from raw behavioral events
Turn prototypes into scalable production ML systems and optimize inference
Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide.
In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring.
Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences.
Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning.
Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent).
Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs.
Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization.
Bachelor’s degree or Master’s degree or equivalent experience in Computer Science, Machine Learning, Data Science, or related field.
5+ years of professional experience building and deploying ML solutions at scale.
Deep understanding of the end-to-end ML lifecycle—from data collection to deployment and monitoring.
Experience in fraud detection, anomaly detection, or behavioral modeling.
Minimum Qualifications - Bachelor’s degree or Master’s degree or equivalent experience in Computer Science, Machine Learning, Data Science, or related field. - 5+ years of professional experience building and deploying ML solutions at scale.
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.
In the employer’s words · Read in context
Likely evergreenReposted 2 times since Apr 10, 2026. A role that keeps coming back is often kept open to collect applications rather than to fill one seat.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications. We count a repost when the same title and location comes back as a new listing within 60 days of the last one coming down. Some hiring systems expire listings on a schedule, so repost rates vary by system.
Day 79
Up longer than most. Similar jobs usually come down between day 8 and day 76.
At Adobe, jobs usually come down by about day 41.
From 5,460 similar postings that came down, and 139 of Adobe’s. Coming down is not always a hire.
31 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- 5+ years of professional experience building and deploying ML solutions at scale. - Strong programming expertise in Python, with hands-on experience in PyTorch, TensorFlow, or similar frameworks. - Deep understanding of the end-to-end ML lifecycle—from data collection to deployment and monitoring.
- Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). - Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. - Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization.
Complete your application on adobe.wd5.myworkdayjobs.com. The employer’s form will show what is required.
Already applied? Track this application
Yes. We’ve followed 2 other Machine Learning Engineer 3 jobs there since April 2026. 2 came down, usually after about 28 days.
New ML Engineer postings at the employers we follow are up 10% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide.
In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring.
The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones.
Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences.
Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning.
Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent).
Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs.
Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization.
Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and production monitoring.
Collaborate cross-functionally with data science, product, and platform teams; mentor junior engineers on experimentation rigor, deployment process, and responsible AI.
Stay current with advances in ML/AI and bring relevant innovations into Adobe's products.
Bachelor’s degree or Master’s degree or equivalent experience in Computer Science, Machine Learning, Data Science, or related field.
5+ years of professional experience building and deploying ML solutions at scale.
Strong programming expertise in Python, with hands-on experience in PyTorch, TensorFlow, or similar frameworks.
Deep understanding of the end-to-end ML lifecycle—from data collection to deployment and monitoring.
Strong grasp of model optimization, inference efficiency, and production system integration.
Experience in fraud detection, anomaly detection, or behavioral modeling.
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.
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Noida, Uttar Pradesh, India
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