Machine Learning Engineer 3

Adobe Systems
Bengaluru
Workplace: OnsiteFull timeFunction: Data Science & Machine LearningExperience: 5+ yearsEducation: bachelorsSkills: ["End-to-end ownership","Cross-functional collaboration","Mentorship","Responsible AI awareness","Innovation mindset"]

Build deep learning models end-to-end to protect Adobe’s ecosystem from fraud, abuse, and misuse. Own the full ML lifecycle—from behavioral data and feature engineering through transformer-based training on large-scale GPU infrastructure, to deployment, monitoring, and inference optimization. Develop in-house behavioral foundation models and production ML systems, collaborating with data science, product, and platform teams while contributing to MLOps and responsible AI practices.

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FursaFursa
Adobe Systems
Adobe Systems
3 days ago

Machine Learning Engineer 3

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 9 hours agoStatus: Live
Reposted: similar role first listed 4 months ago

Job Summary

Build deep learning models end-to-end to protect Adobe’s ecosystem from fraud, abuse, and misuse. Own the full ML lifecycle—from behavioral data and feature engineering through transformer-based training on large-scale GPU infrastructure, to deployment, monitoring, and inference optimization. Develop in-house behavioral foundation models and production ML systems, collaborating with data science, product, and platform teams while contributing to MLOps and responsible AI practices.
Location: Bengaluru
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •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, including event tokenization, temporal/positional embeddings, self-supervised pretraining, and downstream fine-tuning.
  • •Train large models efficiently on GPU infrastructure using mixed-precision, efficient attention, and distributed strategies such as DDP/FSDP.
  • •Build and optimize feature pipelines on Databricks and Spark to transform raw behavioral events into high-quality model inputs.
  • •Translate prototypes into scalable production ML systems and contribute to MLOps practices like experiment tracking, model versioning, CI/CD, automated retraining, and monitoring.

Key Requirements

  • •Bachelor’s or Master’s degree (or equivalent) in Computer Science, Machine Learning, Data Science, or related fields.
  • •5+ years of professional experience building and deploying machine learning solutions at scale.
  • •Strong programming skills in Python, with hands-on experience using 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:5+ years
Education:Bachelor's in Computer Science, Machine Learning, Data Science, or related field
Skills:End-to-end ownershipCross-functional collaborationMentorshipResponsible AI awarenessInnovation mindset
Tech Stack:PythonPyTorchTensorFlowDatabricksSparkTransformersAttention mechanismsGPUMixed-precision trainingGradient accumulationCheckpointingDDPFSDPSelf-supervised learningContrastive learningMasked modelingCI/CDMLOps

Company Brief

Adobe Systems
Provides creative, marketing, and document management software and cloud services, including Photoshop, Illustrator, Acrobat, and the Adobe Experience Cloud, serving creative professionals, enterprises, and governments worldwide.
Industry: SaaS
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: San Jose, United States
Founded: 1982
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