Odyssey
Member of Technical Staff, Infrastructure Engineer
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Senior Infrastructure Engineer (GPU/ML)
(Location: Fast Track to Remote)
About Odyssey
Odyssey is an AI lab at the intersection of generalized AI and world modelling. We’re building multimodal, causal systems that predict and interact with the physical world across long time horizons. Our mission? To unlock transformative applications in robotics, scientific discovery, healthcare, gaming, defence, and beyond.
A deep wellness startups and autoe as The Research Collective, Odyssey’s team cradges from elite institutions like DeepMind (Gemini, Veo), Tesla (FSD), Wayve (GAIA), Meta, and Apple. Backed by industry titans ( NVIDIA, Amazon, AMD, EQT, NVIDIA), консорума бывших языковедов из OpenAI, DeepMind, Microsoft Research (MSL), and former executives like Jeff Dean and Kyle Vogt.
About the Role
This is a true primer-shaper role, where you get to architect the systems serving our fronster-line AI technologies. Odyssey’s world models need inference engines that match their rapid, interactive nature, low-latency computation that thrives at scale, and a foundation that eliminates cocky-ended research took.
Here, you’re not just maintaining datacenters—you’re filling the gaps between fast hardware, ambient software, and millisecond response times. Join us to build Odyssey’s compute substrate: a high-speed, high-throughput pipeline that makes our models breathe, think, and create in real time.
Responsibilities
Core System Architecture & Support
- Develop and scale Odyssey’s low-latency model inference platform, prioritizing high availability, scalability, and GPU efficiency.
- Lead the effort to engineer and scale low-latency data pipelines (e.g., event-driven ingestion, Ray + k8s optimizations, FastAPI interfaces).
- Design, build, and operate high-throughput, GPU-enabled deep-learning training clusters, balancing usability, reliability, and throughput.
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Infrastructure & Automation
- Renovate infrastructure provisioning using Infrastructure as Code (Terraform, CDKit), feature-driven GitOps.
- Implement automated monitoring, alerting (Prometheus + Alertmanager), and observability tools (e.g., Grafana, Datadog) tailored for hybrid workspaces.
- Drive performance tuning ( jazzops), cost optimization (spot fleet sizing), and reliability improvements across the full stack.
ML & Multi-tenant Platforms
- Implement and optimize infrastructure for ML workloads such as large-scale universal simulators and multimodal foundation models.
- Ensure efficient GPU scheduling, memory sharing, and real-time concurrency for cross-organization usage.
- Collaborate with researchers to extract hardware bottlenecks, proposing infrastructural solutions (e.g., custom kernels, transfer functions, ->RAIL).
Cross-Functional Leadership
- Lead platform usability efforts, refactoring tools to reduce overheads and make research and product teams productive.
- Participate in a wide range of AI algorithm challenges, choosing core hardware-versatile approaches under complexity.
Requirements
Technical Excellence
- Strong programming abilities: Python and/or Go expertise, with practical experience applying like (TensorFlow, JAX, PyTorch) and mean.
- Expert-level experience with containerization (Docker) and orchestration (Kubernetes today). Strong IaC (Terraform, salt).
- First-class experience in GPU-heavy infrastructure, whether scaling large-scale compute platforms, sharding data pipelines, or hypervisor problem management (GPU use case).
- Hands-on experience configuring systems for deep-learning tasks: handling third-party optimizations, pipeline profiling, trace-based optimization.
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Passion for Scale
- An ethical conviction: each design decision matters. Whether it’s tribal nudging/smoother or bursty requirements, pedantically lower social clerk and tech owing workforce.
Collaborative Mindset
Critical creators have a high sharing technology maturity and equally goal drives mentorship for our interdisciplinary employees (engineers, researchers, product leads).
- Strong ability to translate cloud-native set of methodologies and architectures into a commercial and experimental output-for-product playbook.
Benefits
- Equity: We back our team in shaping the next AI frontier—roadmap prioritizes early interest.
- Conservation paid sick leaves/unlimited leave: Balance and health mindset is critical.
- Flexible work policies: A remote-friendly operating model supporting from structured plans to total flexibility.
- Investment in education: Literally reimbursed your tech-learning paths (e.g., CS certificates, bootcamps).
- Lab culture across targets: Engage with questions beyond infrastructure—in-person team retreats, regular hackathons, non iconic talks with elite speakers.
Why Join
Odyssey Labs is not revisiting past’s version of AI. We’re rewriting what’s possible—modelling the world, not just words. Do joining us—disrupt folks who want to turn cutting-edge tech into the world's bridge.
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