Member of Technical Staff - Infrastructure en Asari AI

Build AI to co-invent the future

Our mission is to empower people to invent complex systems and solve the world’s hardest problems, working together with scalable and reliable AI agents.

Our team has published award-winning AI research and is backed by top-tier investors including Eric Schmidt, Caltech, Jeff Dean, and JP Millon.

We move fast, think from first principles, and build with purpose. We believe that great results come when people take ownership, grow together, and share both the challenges and the wins.

What you'll do

• Build the core infrastructure driving next-generation AI systems.

• Design and build systems that scale and make optimal trade-offs.

• Shape technical direction and lead critical initiatives.

• Accelerate progress by removing operational and tooling bottlenecks

What you have

Core skills and mindset

• Passion – you live for making systems faster, safer, and smarter.

• Fast learner with clear, effective communication across research and product teams.

• High bar for quality, urgency, and execution — you thrive in a fast-paced environment.

Technical skills

• Strong programming, math, and system-level analytical skills

• Proven experience building reliable, scalable ML infrastructure

• Fluency in at least one scripting language (e.g., Python) or low-level language (e.g., C++, Rust).

• Hands-on experience with (or strong ability to quickly learn) to use modern infra stacks, including:

  • Containerization & orchestration: Docker, Kubernetes

  • Infrastructure-as-Code: Terraform, Pulumi

  • CI/CD: GitHub Actions, Jenkins, or similar

  • Observability: Prometheus, Grafana, OpenTelemetry

  • Distributed systems: Kafka, Ray, Redis, gRPC

  • Model training and inference: PyTorch, DeepSpeed, JAX/XLA, TensorRT, vLLM

• Strong grasp of networking, storage, and compute fundamentals, including performance tuning and debugging.

• Experience with using AI assistants in complex engineering environments.

Bonus points

• Open-source contributions or ML-related projects.

• Experience with high-performance software infrastructure in production environments.

• Practical experience with deep learning, reinforcement learning, or unsupervised learning.

• Familiarity with distributed training systems, model serving platforms, and MLOps frameworks (e.g., Kubeflow, MLflow, BentoML).

• Knowledge of security, compliance, or reliability for AI/ML systems.

Our compensation, benefits, and perks

We offer competitive compensation + stock options, full health coverage, and a 401(k) match, plus additional wellness perks, flexible hours, and unlimited PTO. We prioritize growth and connection through daily meals in office, learning budgets, and regular team socials.