Senior Machine Learning Engineer leading ML model development for Adobe's Content Intelligence team. Collaborating with cross - functional teams to enhance creative content understanding using advanced AI.
About the role
- MLOps Engineer responsible for managing PyTorch-based training and inference workloads at Menlo HQ. Building and maintaining robust infrastructure for AI models and optimization processes.
Responsibilities
- Own and evolve the infrastructure behind PyTorch-based training and inference workloads
- Build and maintain training and inference pipelines using PyTorch
- Own and evolve inference serving infrastructure
- Write and maintain robust tooling in Python and C++
- Optimize compute workloads for bare-metal environments
- Troubleshoot low-level networking issues
- Set up and manage ML environments
- Establish CI/CD patterns for AI workloads
- Integrate monitoring, alerting, and incident response
Requirements
- Deep expertise in PyTorch internals
- Strong programming skills in Python and C++
- Solid computer science fundamentals
- Hands-on experience with vLLM and SGLang
- Experience with RLHF and PPO training pipelines
- Strong understanding of distributed training setups
- Experience debugging and tuning bare-metal Linux servers
- Familiarity with job schedulers such as Airflow
- Strong grasp of containerized and cloud-native environments
Benefits
- Flexibility in work arrangements
- Professional development opportunities
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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