Member of Technical Staff, Inference & RL Systems

About the role As a Software Engineer on the Inference & RL Systems team, you will design and operate the distributed systems that serve our models in production and power large-scale post-training workflows. This role sits at the boundary between model execution and distributed infrastructure. You will work on systems that determine inference latency, throughput, stability, and the reliability of RL and post-training training loops. Magic’s long-context models introduce demanding execution constraints: KV-cache scaling, memory pressure under long sequences, batching trade-offs, long-horizon trajectory rollouts, and sustained throughput under real-world workloads. You will own the infrastructure that makes both production inference and large-scale RL iteration fast and reliable. What you’ll work on Design and scale high-performance inference serving systems Optimize KV-cache management, batching strategies, and scheduling Improve throughput and latency for long-context workloads Build and maintain distributed RL and post-training infrastructure Improve reliability of rollout, evaluation, and reward pipelines Automate fault detection and recovery for serving and RL systems Profile and eliminate performance bottlenecks across GPU, networking, and storage layers Collaborate with Kernels and Research to align execution systems with model architecture What we’re looking for Strong software engineering and distributed systems fundamentals Experience building or operating large-scale inference or training systems Deep understanding of GPU execution constraints and memory trade-offs Experience debugging performance issues in production ML systems Ability to reason about system-level trade-offs between latency, throughput, and cost Track record of owning critical production infrastructure Compensation, benefits, and perks (US) Annual salary range: $225K - $550K Equity is a significant part of total compensation, in addition to salary 401(k) plan with 6% salary matching Generous health, dental and vision insurance for you and your dependents Unlimited paid time off Visa sponsorship and relocation stipend to bring you to SF, if possible A small, fast-paced, highly focused team Magic strives to be the place where high-potential individuals can do their best work. We value quick learning and grit just as much as skill and experience. #J-18808-Ljbffr Magic