Find jobs
Pricing
Sign in
FIND JOBS
PRICING
SIGN IN
SIGN UP
← Back
GE
Genesis
Inference
Save
Tailor resume
Apply
Location
Paris
Work mode
hybrid
Type
full-time
Department
Engineering & Research
Company size
51+ people
First seen
4mo ago
Last seen
2d ago
What You’ll Do
Responsibilities
•
Build low-latency inference pipelines for on-device deployment, enabling real-time next-token and diffusion-based control loops in robotics
•
Design and optimize distributed inference systems on GPU clusters, pushing throughput with large-batch serving and efficient resource utilization
•
Implement efficient low-level code (CUDA, Triton, custom kernels) and integrate it seamlessly into high-level frameworks
•
Optimize workloads for both throughput (batching, scheduling, quantization) and latency (caching, memory management, graph compilation)
•
Develop monitoring and debugging tools to guarantee reliability, determinism, and rapid diagnosis of regressions across both stacks
What You’ll Bring
Requirements
•
Deep experience in distributed systems, ML infrastructure, or high-performance serving (8+ years)
•
Production-grade expertise in Python, with strong background in systems languages (C++/Rust/Go)
•
Low-level performance mastery: CUDA, Triton, kernel optimization, quantization, memory and compute scheduling
•
Proven track record scaling inference workloads in both throughput-oriented cluster environments and latency-critical on-device deployments
•
System-level mindset with a history of tuning hardware–software interactions for maximum efficiency, throughput, and responsiveness
More roles at Genesis
Senior Asset Pipeline Engineer, Sim-Ready Content
Robot Learning
Training / AI Infrastructure
ML Compiler & System
Foundation Models
Seekless
Product
Find jobs
Companies
Pricing
Legal
Privacy
Terms
Cookies
© 2026 SEEKLESS, INC. ALL RIGHTS RESERVED.
BUILT WITH CARE