- Salary
- $130k – $170k/yr
- Location
- San Francisco, California, US
- Workplace
- Remote
- Type
- Full-time
- Department
- Engineering
- Education
- PhD
- Source
- Y Combinator
Description
About the Role
DeepAware AI (YC S25) is building secure, efficient, and autonomous infrastructure for the AI era. As an AI/ML Engineer, you’ll design, build, and deploy machine learning models that power our next-generation Data Center Infrastructure Management (DCIM) platform. Your work will focus on reinforcement learning for intelligent workload scheduling, optimization algorithms for energy and cost savings, and anomaly detection to prevent downtime and enhance security.
You’ll be joining a fast-moving, technically ambitious team tackling some of the most complex real-world AI problems at the intersection of computing, energy, and robotics.
Responsibilities
- Develop and refine reinforcement learning models for GPU workload placement and power optimization
- Implement anomaly detection pipelines for real-time threat detection and failure alerts
- Collaborate with data engineers to ensure high-quality, production-ready datasets
- Benchmark models against industry baselines and integrate them into our production systems
- Contribute to overall architecture and deployment strategies for large-scale AI infrastructure
Requirements
- Strong background in machine learning; hands-on experience with reinforcement learning techniques
- Proficiency in Python and PyTorch or TensorFlow
- Experience with distributed training and deployment in production environments
- Familiarity with energy systems, scheduling algorithms, or operations research is a plus
- Ability to thrive in a startup environment — ownership mindset, adaptability, and collaborative spirit
Nice-to-Have
- Experience with NVIDIA CUDA/cuDNN, Triton Inference Server, or ROS2 for robotics integration
- Knowledge of data center operations or AI infrastructure optimization
Location:
San Francisco Bay Area preferred; remote considered for exceptional candidates
Why DeepAware?
You’ll be working on problems that directly impact the sustainability and reliability of the world’s AI infrastructure — with a team that values technical excellence, creativity, and impact.
