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Senior Applied Scientist - Machine Learning Systems Engineer - Adobe Systems
ML Engineer
Senior ML Systems Engineer driving production‑ready inference performance, latency reduction, and cost efficiency for image‑editing software using Python, C++, CUDA, and modern deep‑learning frameworks.
About the role
Key Responsibilities
- Design, implement, and optimize end‑to‑end machine‑learning inference pipelines for photo‑editing applications.
- Collaborate with model architects to reshape model architectures for maximum runtime efficiency on GPU and CPU platforms.
- Develop and maintain high‑performance inference runtimes, leveraging CUDA, low‑level C++, and profiling tools.
- Build scalable services and tooling for model deployment, monitoring, and cost‑aware resource management.
- Conduct performance analysis, latency benchmarking, and cost modeling to guide engineering trade‑offs.
Requirements
- 5+ years of experience in machine‑learning systems engineering, with strong proficiency in Python and C++.
- Deep knowledge of GPU programming (CUDA) and performance optimization techniques for large‑scale inference.
- Hands‑on experience with TensorFlow or PyTorch and deploying models in production environments.
- Proven ability to design distributed, low‑latency services and to profile/optimize code for speed and cost.
- Strong problem‑solving skills, ability to work cross‑functionally, and a track record of delivering production‑ready ML solutions.
Skills
pythonccudatensorflowpytorch