Machine Learning Engineer 5
Adobe · Bangalore, India · Design
mid
Machine Learning Engineer
ic
· Posted May 12, 2026
Skills
About this role
Adobe is hiring a mid-level Machine Learning Engineer based in Bangalore, India. The posting calls out experience with Python, PyTorch, Hugging Face, MLflow.
- Role
- Machine Learning Engineer
- Function
- machine learning
- Level
- mid
- Track
- Individual contributor
- Employment
- Full-time
- Location
- Bangalore, India
- Department
- Design
- Posted
- May 12, 2026
More roles at Adobe
GTM Operations Senior Manager
San Francisco, CA · senior
Express Salesforce Data Analytics
Senior Partner Sales Account Manager - Global System Integrator
Remote (Germany) · senior
Express
Manager, Cloud Security
Lehi, UT · manager
Python Rust Ruby
Sr Product Security Engineer
Seattle, WA · senior
Python Express Terraform
Principal Enterprise Architect Professional Services (Madrid)
Madrid, Spain · principal
Express
All Adobe jobs →
Job description
from Adobe careersAbout the Role
We are looking for a Senior Machine Learning Engineer with deep expertise in generative modeling and computer vision to join Adobe's Applied AI team. In this role, you will architect and ship state-of-the-art diffusion-based models, drive applied research into production, and mentor a team of talented engineers. You will work at the intersection of cutting-edge research and real-world impact — translating the latest advances in generative AI into scalable, reliable systems.
Key Responsibilities
Generative Modeling
- Design, train, and fine-tune large-scale diffusion models (DDPM, DDIM, LDM, DiT) for image, video, and multimodal generation tasks.
- Drive improvements in sampling efficiency — distillation, consistency models, progressive training, and guided generation techniques.
- Stay current with and rapidly prototype ideas emerging from the broader AI community.
Computer Vision & Perception
- Build production-grade pipelines for image/video understanding: segmentation, detection, depth estimation, optical flow, and 3D reconstruction.
- Develop and fine-tune vision foundation models (ViT, CLIP, DINOv2, SAM) for downstream tasks using parameter-efficient methods (LoRA, adapters).
- Integrate vision encoders with generative backbones for controllable generation (ControlNet, IP-Adapter, inpainting, editing).
Applied ML & Systems
- Own the full ML lifecycle: data curation, experiment tracking, model evaluation, optimization, deployment, and monitoring.
- Optimize models for inference: quantization (INT8/FP8), ONNX export, Flash Attention, and xFormers.
This is an excerpt. Read the full job description on Adobe careers →