1 day ago
Helsinki, FinlandSenior
Responsibilities
- Design and develop agentic AI frameworks supporting planning, tool use, memory, reasoning, and long-running workflows.
- Automate environment setup, containerization, dependency management, and reproducible workload deployment.
- Compose and launch scheduler-based workloads using resource-aware configurations and operational policies.
- Investigate failures with logs, telemetry, and system information, and develop safe automated remediation approaches.
- Profile applications and workloads to identify bottlenecks and optimization opportunities.
- Benchmark and validate performance improvements using robust, reproducible methods.
- Optimize applications, libraries, runtimes, compilers, and GPU kernels.
- Build testing, observability, validation, rollback, and performance-regression mechanisms.
- Apply emerging agentic AI technologies to engineering workflows and collaborate with platform, performance, compiler, runtime, AI, and application teams.
Requirements
- Master’s or PhD in Computer Science, Computer Engineering, Electrical Engineering, or a related technical discipline, or equivalent practical experience.
- Experience developing and deploying agentic AI or autonomous software systems involving orchestration, planning, tool use, memory, or long-running workflows.
- Experience building or integrating LLM inference and serving solutions on-premises or through cloud services.
- Strong Python programming experience and experience with at least one systems programming language such as C, C++, Rust, or Go.
- Experience building reliable production software using evaluation frameworks, regression testing, observability, structured debugging, and related engineering practices.
- Experience connecting automation or AI systems with build and test systems, code execution environments, schedulers, APIs, or telemetry platforms.
- Preferred experience with HPC environments, Slurm, Kubernetes, multi-node GPU workloads, or container platforms.
- Preferred experience with GPU profiling, ROCm, CUDA, LLM training or fine-tuning, GPU kernel development, Triton, HIP, compiler technologies, MLIR, LLVM, or XLA.
- Preferred experience with performance optimization, performance portability, numerical validation, and emerging agentic AI techniques.
Benefits
- AMD states that benefits are offered and refers applicants to “AMD benefits at a glance.”
Tech Stack
Categories
About AMD
AMD designs and sells CPUs, GPUs, and adaptive/embedded computing products for PCs, data centers, gaming, and edge devices. Its portfolio includes Ryzen and EPYC processors, Radeon and Instinct graphics, and adaptive SoCs from its Xilinx acquisition, sold to OEMs, cloud providers, and device makers. Founded in 1969 and headquartered in Santa Clara, it is a public company on NASDAQ and supplies semi-custom chips for major game consoles.