Machine Learning Engineer

Adobe Systems
Bengaluru
Workplace: OnsiteFull timeFunction: Data Science & Machine LearningExperience: 4-8 yearsEducation: bachelorsSkills: ["Cross-functional collaboration","Mentorship","Responsible AI","Experiment rigor","Model/production ownership"]

Build deep learning and foundation models that power Adobe’s administration capabilities, from model design and training to production deployment and monitoring. Own the end-to-end ML lifecycle—data/event processing, embeddings, self-supervised pretraining, fine-tuning, and efficient GPU training. Create feature pipelines on Databricks/Spark and deliver scalable, observable inference systems while contributing to MLOps practices and responsible AI.

Loading

Loading job details...

Preparing the role view and application actions.

FursaFursa
Adobe Systems
Adobe Systems
1 day ago

Machine Learning Engineer

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI
Last checked: 35 minutes agoStatus: Live
Reposted: similar role first listed 3 weeks ago

Job Summary

Build deep learning and foundation models that power Adobe’s administration capabilities, from model design and training to production deployment and monitoring. Own the end-to-end ML lifecycle—data/event processing, embeddings, self-supervised pretraining, fine-tuning, and efficient GPU training. Create feature pipelines on Databricks/Spark and deliver scalable, observable inference systems while contributing to MLOps practices and responsible AI.
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/attention architectures for long behavioral event sequences.
  • •Own the full training stack: event tokenization, temporal/positional embeddings, self-supervised pretraining, and downstream fine-tuning.
  • •Train large models efficiently on GPU infrastructure using mixed-precision, gradient accumulation/check-pointing, efficient attention, and distributed strategies (DDP/FSDP).
  • •Build and optimize feature pipelines on Databricks and Spark to transform behavioral events into high-quality model inputs.
  • •Translate prototypes into production ML systems and contribute to MLOps practices (experiment tracking, versioning, CI/CD, retraining, and monitoring), while collaborating and mentoring across teams.

Key Requirements

  • •Bachelor’s or Master’s degree (or equivalent) in Computer Science, Machine Learning, Data Science, or a related field.
  • •4–8 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 through deployment and monitoring.
  • •Strong grasp of model optimization, inference efficiency, and production system integration.
Experience:4-8 years
Education:Bachelor's in Computer Science, Machine Learning, Data Science, or related field
Skills:Cross-functional collaborationMentorshipResponsible AIExperiment rigorModel/production ownership
Tech Stack:PythonPyTorchTensorFlowDeep learningTransformerAttentionGPUMixed-precision trainingGradient accumulationCheckpointingEfficient attentionDDPFSDPDatabricksSparkMLOpsExperiment trackingModel versioningCI/CDAutomated retraining

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
Glassdoor
Glassdoor: 4.0
WebsiteLinkedInGlassdoor