About DeepAware AI

Make AI data centers more efficient.

Tech description:

We’re building a Data Center Infrastructure Management (DCIM) platform that uses Reinforcement Learning for workload scheduling, real-time market integration for energy cost optimization, and AI-driven monitoring for security and stability. Our upcoming robotics integration enables remote inspections, cable swaps, and maintenance — enabling true 24/7 autonomous operations. You’ll work on hard, high-impact technical problems — from designing scalable real-time control systems to optimizing GPU workloads across multi-tenant environments, to building the “robotic hands” of AI infrastructure.

Job 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.

DeepAware AI remote jobs

Business Development Manager

Robotics Engineer

AI/ML Engineer