Ai/ml Performance Engineer - Gpu Optimization Job at AMD (Helsinki)

Senior Manager, Performance AI/ML Network Deployment Engineering

The Senior Manager, DC GPU Advanced Forward Deployment and Systems Engineering i...

Location

United States , Santa Clara

Salary:

210400.00 - 315600.00 USD / Year

AMD

Expiration Date

Until further notice

Requirements

Expertise in networking and performance optimization for large-scale AI/ML networks, including network, compute, storage cluster design, modelling, analytics, performance tuning, convergence, scalability improvements
Prefer candidates with solid, hands-on expertise in at least one or more of 3 domains, namely compute, network, storage
Experience in working with large customers such as Cloud Service Providers and global enterprise customers
Proven leadership in engaging customers with diverse technical disciplines in avenues such as Proof of Concept, Competitive evaluations, Early Field Trials etc
Direct experience in working with large customers and can operate with sense of urgency, own the problems and resolve it
Demonstrated leadership in network architecture, hands on experience in RoCEv2 Design, VXLAN-EVPN, BGP, and Lossless Fabrics
Proven ability to influence design and technology roadmaps, leveraging a deep understanding of datacenter products and market trends
Extensive hands-on Network deployment expertise and proven track record of delivering large projects on time. Cisco, Juniper or Arista experience is preferred
Direct, co-development/deployment experience in working with strategic customers/partners in bringing solutions to market
Excellent communication level from engineer to mid-management to C-level of audience

Job Responsibility

Collaborate with strategic customers on scalable designs involving compute, networking, storage environment, work with industry partners, Internal teams to accelerate the deployment, adoption of various AI/ML models
Engage system-level triage and at-scale debug of complex issues across hardware, firmware, and software, ensuring rapid resolution and system reliability
Drive the ramp of Instinct-based large scale AI datacenter infrastructure based on NPI base platform hardware with ROCm, scaling up to pod and cluster level, leveraging the best in network architecture for AI/ML workloads
Enhance tools and methodologies for large-scale deployments to meet customer uptime goals and exceed performance expectations
Engage with clients to deeply understand their technical needs, ensuring their satisfaction with tailored solutions that leverage your past experience in strategic customer engagements and architectural wins
Provide domain specific knowledge to other groups at AMD, share the lessons learnt to drive continuous improvement
Engage with AMD product groups to drive resolution of application and customer issues
Develop and present training materials to internal audiences, at customer venues, and at industry conferences

New

Principal Software Engineer

Microsoft Advertising is seeking a Principal Software Engineer to join our Ads E...

Location

United States , Redmond

Salary:

139900.00 - 274800.00 USD / Year

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
OR equivalent experience
Master's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
OR Bachelor's Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
OR equivalent experience
Industry experience in advertising or search engine backend systems, such as large-scale ad ranking, real-time bidding (RTB), or relevance-serving infrastructure
Hands-on experience with real-time data streaming systems (Kafka, Flink, Spark Streaming), feature-store integration, and multi-region deployment for low-latency, globally distributed services
Familiarity with LLM inference optimization—model sharding, tensor/kv-cache parallelism, paged attention, continuous batching, quantization (AWQ/FP8), and hybrid CPU–GPU orchestration
Demonstrated success operating large-scale systems with SLA-based capacity forecasting, autoscaling, and performance telemetry
proven leadership in cross-functional architecture initiatives and technical mentorship

Job Responsibility

Design and lead the development of large-scale, distributed online serving systems—including GPU-accelerated and CPU-based ranking/inference pipelines—to process millions of ad requests per second with ultra-low latency, high throughput, and solid reliability
Architect and optimize end-to-end inference infrastructure, including model serving, batching/streaming, caching, scheduling, and resource orchestration across heterogeneous hardware (GPU, CPU, and memory tiers)
Profile and optimize performance across the full stack—from CUDA kernels and GPU pipelines to CPU threads and OS-level scheduling—identifying bottlenecks, tuning latency tails, and improving cost efficiency through advanced profiling and instrumentation
Own live-site reliability as a DRI: design telemetry, alerting, and fault-tolerance mechanisms
drive rapid diagnosis and mitigation of performance regressions or outages in globally distributed systems
Collaborate and mentor across teams—driving architecture reviews, enforcing engineering excellence, promoting system-level optimization practices, and mentoring others in deep debugging, profiling, and performance engineering

Fulltime

Performance Architect

In this position, you will develop AI Storage Solutions based advanced system ar...

Location

United States , Milpitas

Salary:

136537.00 - 193442.00 USD / Year

Sandisk

Expiration Date

April 28, 2026

Requirements

Bachelors or Masters or PhD in Computer/Electrical Engineering with 5+ years of relevant experience in Performance Modeling, Simulation, and Analysis using SystemC
At least 5+ years of experience with SystemC modeling
Good understanding of computer/graphics architecture, ML, LLM
Experience of simulation using System C and TLM, behavioral modeling and performance analysis

Job Responsibility

Build SystemC performance models for AI Storage Solutions based products covering end-to-end from GPU/TPU/NPU/xPU, host interface, memory hierarchy, basedie controller, and AI Storage Solutions using various packaging technolgies
Responsible for improving the AI/ML ASIC Architecture performance through hardware & software co-optimization, post-silicon performance analysis, and influencing the strategic product roadmap
Workload analysis and characterization of ASIC and competitive datacenter and AI solutions to identify opportunities for performance improvement in our products
Collaboration with Architecture team to resolve performance issues and optimize the performance and TCO of their AI Storage Solutions based datacenter technologies
Experience modeling one or some components of AI/ML accelerator ASICs such as AI Storage Solutions, PCIe/UCIe/CXL, NoC, DMA, Firmware Interactions, NAND, xPU, fabrics, etc
Performance modeling and optimization for multi-trillion parameter LLM training/inference including Dense, Mixture of Experts (MoE) with multiple modalities (text, vision, speech)
Model/optimize novel parallelization strategies across tensor, pipeline, context, expert and data parallel dimensions
Architect memory-efficient training systems utilizing techniques like structured pruning, quantization (MX formats), continuous batching/chunked prefill, speculative decoding
Incorporate and extend SOTA models such as GPT-4, Reasoning models like Deepseek-R1, and multi-modal architectures
Collaborate with internal and external stakeholders/ML researchers to disseminate results and iterate at rapid pace

What we offer

Short-Term Incentive (STI) Plan
Long-Term Incentive (LTI) program (restricted stock units (RSUs) or cash equivalents)
RSU awards for eligible new hires
Paid vacation time
Paid sick leave
Medical/dental/vision insurance
Life, accident and disability insurance
Tax-advantaged flexible spending and health savings accounts
Employee assistance program
Other voluntary benefit programs such as supplemental life and AD&D, legal plan, pet insurance, critical illness, accident and hospital indemnity

Fulltime

Director Software Development

At AMD, we are enabling the next generation of AI innovation by leveraging the p...

Location

China , Shanghai

Salary:

Not provided

AMD

Expiration Date

Until further notice

Requirements

10+ years in AI/ML software development
5+ years in leadership roles managing AI model enablement or optimization teams
Expertise in optimizing real-time AI models for deep learning applications (computer vision, NLP, etc.)
Proficiency with AI frameworks (TensorFlow, PyTorch, ONNX Runtime, JAX, Triton) and their optimization for GPU architectures
Strong background in optimizing software for AMD GPUs or similar high-performance platforms
Familiarity with ROCm is a plus
Proven experience with performance optimization, benchmarking, and scaling AI models on GPUs
Exceptional ability to collaborate cross-functionally and define long-term strategies for AI/ML innovation
Strong verbal and written communication skills, with experience presenting to senior leadership and working with customers and partners
Advanced degree (Master’s or PhD) in Computer Science, Electrical Engineering, AI/ML, or related field

Job Responsibility

Lead and develop teams responsible for AI inference model enablement and optimization
Direct efforts to optimize AI frameworks for seamless compatibility and performance on AMD GPUs (Instinct, Navi)
Oversee benchmarking, performance tuning, and optimization of AI inference models to improve latency, throughput, and efficiency on AMD hardware
Partner with hardware, software, and QA teams to ensure tight integration of AI frameworks with ROCm for maximum performance
Drive AI model optimization innovations, enhancing the speed, efficiency, and scalability of AI workloads
Lead the vision and strategy for optimizing AI inference on AMD GPUs
Collaborate with customers and open-source communities to ensure that AMD’s AI solutions meet industry needs, fostering contributions to MIGraphX, vLLM, and other AMD AI Framework Inference teams
Oversee automation frameworks to streamline model integration and performance testing, ensuring scalability across diverse AI workloads

New

AI Systems Engineer – AI Model (Training & Inference)

The AMD AI Group is looking for a Senior Software Development Engineer to own th...

Location

Canada , Markham

Salary:

106400.00 - 159600.00 CAD / Year

AMD

Expiration Date

Until further notice

Requirements

Industry experience shipping production AI/ML infrastructure, with hands-on work spanning both training and inference.
Bachelor’s or Master’s degree or Ph.D in Computer/Software Engineering, Computer Science, or related technical discipline

Job Responsibility

Enable and optimize large-scale model training (LLMs, VLMs, MoE architectures) on AMD Instinct GPU clusters, ensuring correctness, reproducibility, and competitive throughput.
Build and maintain training infrastructure: job orchestration, distributed checkpointing, data loading pipelines, and storage optimization for multi-thousand GPU clusters on Kubernetes.
Debug and resolve training-specific issues including gradient norm explosions, non-deterministic behavior across GPU generations, and compute-communication overlap in distributed training (FSDP, DeepSpeed, Megatron-LM).
Optimize RCCL collective communication patterns for training workloads, including all-reduce, all-gather, and reduce-scatter across multi-node topologies.
Develop monitoring, alerting, and compliance infrastructure to ensure training cluster health, data security, and SLA adherence at scale.
Design and build end-to-end validation and testing infrastructure using proxy workloads, synthetic benchmarks, and configurable workload generators to systematically validate platform readiness across AMD Instinct GPU generations.
Write and optimize high-performance GPU kernels (GEMM, attention, quantized matmul, GPTQ/AWQ) in HIP, Triton, and MLIR targeting AMD Instinct architectures, with demonstrated ability to outperform open-source baselines.
Drive end-to-end inference enablement on new AMD GPU silicon - be among the first to get frontier models running on each new Instinct generation, creating reproducible guides and reference implementations.
Optimize inference serving frameworks (vLLM, SGLang, TorchServe) for AMD GPUs: batching strategies, KV-cache management, speculative decoding, and continuous batching for production throughput/latency targets.
Develop novel approaches to inference acceleration, including bio-inspired algorithms, SLM-assisted batching, and custom scheduling strategies that exploit AMD hardware characteristics.

Fulltime

Senior Devops & AI Engineer

This role presents a unique opportunity to contribute to the future of impactful...

Location

India , Hyderabad

Salary:

Not provided

Fission Labs

Expiration Date

Until further notice

Requirements

Bachelor's degree in Computer Science, Engineering, or related field
6+ years of experience in Infrastructure Mgmt. roles, with a focus on cloud platforms (Azure and AWS Preferred)
Hands-on experience with operations (DevSecOps) principles and best practices
Proficiency in scripting languages such as Python, PowerShell, or Bash
Excellent communication and collaboration skills
In-depth knowledge of Linux operating systems, including CentOS, Ubuntu, and Red Hat, with expertise in shell scripting, package management, and system administration
Hands-on experience with a wide range of AWS and Azure services
Develop and maintain Infrastructure as Code (IAC) templates using tools such as Terraform or AWS CloudFormation
Experience setting up cloud infrastructure stack, databases, service endpoints, GPU as well as CPU resource scaling, optimization etc.
Should have worked AIOps/MLOP

Job Responsibility

Configure and optimize Linux-based servers for performance, security, and resource utilization, including kernel tuning, file system management, and network configuration
Architect cloud solutions leveraging best practices and services offered by AWS and Azure, optimizing for scalability, reliability, and cost-effectiveness
Implement and manage hybrid cloud environments, facilitating seamless integration and interoperability between AWS and Azure services
Establish version control practices for IAC templates, ensuring traceability, auditability, and reproducibility of infrastructure changes

What we offer

Opportunity to work on impactful technical challenges with global reach
Vast opportunities for self-development, including online university access and knowledge sharing opportunities
Sponsored Tech Talks & Hackathons to foster innovation and learning
Generous benefits packages including health insurance, retirement benefits, flexible work hours, and more
Supportive work environment with forums to explore passions beyond work

Fulltime

Staff Software Engineer, GPU Infrastructure (HPC)

The internal infrastructure team is responsible for building world-class infrast...

Location

Salary:

Not provided

Cohere

Expiration Date

Until further notice

Requirements

Deep expertise in ML/HPC infrastructure: Experience with GPU/TPU clusters, distributed training frameworks (JAX, PyTorch, TensorFlow), and high-performance computing (HPC) environments
Kubernetes at scale: Proven ability to deploy, manage, and troubleshoot cloud-native Kubernetes clusters for AI workloads
Strong programming skills: Proficiency in Python (for ML tooling) and Go (for systems engineering), with a preference for open-source contributions over reinventing solutions
Low-level systems knowledge: Familiarity with Linux internals, RDMA networking, and performance optimization for ML workloads
Research collaboration experience: A track record of working closely with AI researchers or ML engineers to solve infrastructure challenges
Self-directed problem-solving: The ability to identify bottlenecks, propose solutions, and drive impact in a fast-paced environment

Job Responsibility

Build and scale ML-optimized HPC infrastructure: Deploy and manage Kubernetes-based GPU/TPU superclusters across multiple clouds, ensuring high throughput and low-latency performance for AI workloads
Optimize for AI/ML training: Collaborate with cloud providers to fine-tune infrastructure for cost efficiency, reliability, and performance, leveraging technologies like RDMA, NCCL, and high-speed interconnects
Troubleshoot and resolve complex issues: Proactively identify and resolve infrastructure bottlenecks, performance degradation, and system failures to ensure minimal disruption to AI/ML workflows
Enable researchers with self-service tools: Design intuitive interfaces and workflows that allow researchers to monitor, debug, and optimize their training jobs independently
Drive innovation in ML infrastructure: Work closely with AI researchers to understand emerging needs (e.g., JAX, PyTorch, distributed training) and translate them into robust, scalable infrastructure solutions
Champion best practices: Advocate for observability, automation, and infrastructure-as-code (IaC) across the organization, ensuring systems are maintainable and resilient
Mentorship and collaboration: Share expertise through code reviews, documentation, and cross-team collaboration, fostering a culture of knowledge transfer and engineering excellence

What we offer

An open and inclusive culture and work environment
Work closely with a team on the cutting edge of AI research
Weekly lunch stipend, in-office lunches & snacks
Full health and dental benefits, including a separate budget to take care of your mental health
100% Parental Leave top-up for up to 6 months
Personal enrichment benefits towards arts and culture, fitness and well-being, quality time, and workspace improvement
Remote-flexible, offices in Toronto, New York, San Francisco, London and Paris, as well as a co-working stipend
6 weeks of vacation (30 working days!)

Fulltime

Product Application Engineer - Data Center Deployment

This highly technical role supports large-scale datacenter graphics hardware and...

Location

United States , Santa Clara; Austin; Secaucus

Salary:

160960.00 - 241440.00 USD / Year

AMD

Expiration Date

Until further notice

Requirements

Datacenter customer support in virtualization-focused environments
Virtual environments (VMWare, Citrix, KVM, Microsoft, and others) and virtual machine configuration/management
Data storage, protection, deduplication, and storage-related network optimization especially with Weka, DDN, and VAST products
Working in or closely with a deployment services organization utilizing tools like Salesforce, JIRA and Confluence
Linux installation, configuration, debugging, and performance tuning
Debugging, root-cause analysis, and system-level problem solving
Site reliability engineering concepts and best practices
Server architecture, remote management, network topologies, and compute subsystem operations
Datacenter GPU software stacks such as ROCm™ or CUDA
High-performance networks for HPC and AI (RDMA/RoCE, InfiniBand)

Job Responsibility

Design, optimize, and troubleshoot virtualization solutions for high-performance datacenter GPU, CPU, and related platforms
Support customers, partners, and internal teams on virtualization topics related to AI and Machine Learning workloads
Build and configure datacenter networking environments for customer testing, validation, and deployment
Qualify and assess new virtualization capabilities to ensure alignment with customer and product requirements
Provide mentorship and technical guidance to junior engineering staff
Partner with development teams to identify and resolve hardware/software issues from early bring-up through end-of-life
Document and escalate technical issues following established procedures
Collaborate with program managers to maintain schedules, track action items, and ensure deliverables are met
Provide clear project status updates to internal leadership and customer stakeholders
Build a deep understanding of customer goals to ensure impactful technical guidance and solution delivery

Fulltime

Ai/ml Performance Engineer - Gpu Optimization

AMD

Location:
Finland , Helsinki

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Job Description:

Job Responsibility:

Requirements:

Nice to have:

Additional Information:

Job Posted:
April 16, 2026

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