AI Infrastructure

Expert Infrastructure Recruitment for Teams Building and Operating AI at Scale

DeepRec.ai supports organisations designing, building, and scaling AI infrastructure that underpins production machine learning and inference platforms in use today. Our AI infrastructure practice focuses on supporting companies hiring specialist engineers across compute, platforms, and systems, where architecture, performance, efficiency, and reliability determine whether AI systems succeed outside the lab.

As AI models move into real-world use, AI infrastructure has become the defining challenge of production AI. Organisations are under increasing pressure to provision, orchestrate, and operate compute and data platforms at scale, meeting strict requirements around latency, throughput, cost, and availability. This has driven unprecedented demand for AI infrastructure capability, and for engineers who can build and operate the systems that inference, training, and experimentation depend on.

DeepRec.ai’s recruitment consultants work closely with teams operating at this level of complexity, giving us a clear view of the skills, experience, and systems required to build production-grade AI. Whether that’s AI platform engineering, GPU and accelerator infrastructure, distributed systems, or inference at scale, we connect organisations with AI engineers who can operate effectively in real-world environments.

Hire AI Infrastructure Talent:

Talk to a Consultant

Find a Job in AI Infrastructure: 

Explore Careers

Why do Leading AI Teams Choose DeepRec.ai for AI Infrastructure Hiring?

DeepRec.ai's specialist Infra consultants are trusted by tech pioneers across the UK, Ireland, Germany, Switzerland, and the United States.

Our consultants work directly with teams building and operating production AI systems, giving us first-hand exposure to the architectures, constraints, and trade-offs involved.

Our consultants work directly with teams building and operating AI platforms and infrastructure in production, giving us first-hand exposure to the architectures, trade-offs, and operational realities involved.

This includes teams working on distributed training and inference, high-performance computing, GPU and accelerator clusters, and AI platform reliability, where system-level performance and infrastructure design are critical to deploying AI systems at scale.

Dedicated AI Infrastructure Delivery Teams

DeepRec.ai operates through dedicated divisions and delivery teams, each focused on a specific area of deep tech. This structure allows our AI infrastructure practice to work with depth and continuity, rather than spreading expertise across unrelated markets.

We speak Deep Tech

AI infrastructure is not a generic hiring problem. When you need to hire niche AI talent, you need a specialist who speaks deep tech. We know our serving systems from our pipelines, and we know how to talk about them with top-tier candidates. 

Cross-border hiring expertise

As part of Trinnovo Group, which holds SECO and AUG licenses, we can provide compliant cross-border recruitment and employment services across Switzerland and Germany. In addition to permanent hiring, we can payroll talent in-house and manage the full administrative and compliance burden on behalf of our clients. This is supported by an internal compliance team, ensuring hiring processes remain robust, transparent, and aligned with local regulatory requirements.

A Deep Tech Community

Much of the most in-demand AI infrastructure talent does not engage with traditional hiring channels. Through sustained involvement in the deep tech ecosystem, including events, collaboration, and research, DeepRec.ai maintains close ties to the AI infrastructure community, enabling trusted access to engineers and technical leaders who are typically difficult to reach through conventional recruitment. Find out more about DeepRec.ai's social hub here.

A Perfect Client Net Promoter Score (+100)

DeepRec.ai maintains a client Net Promoter Score of +100 based on client feedback, a reflection of consistent delivery, clear communication, and long-term partnerships built on trust. For our clients, this typically reflects a recruitment experience that is focused, technically credible, and aligned with the realities of hiring in complex, talent-constrained deep tech markets.

AI Infrastructure Salary Guide

Q1 2026 base salary benchmarks for ML systems, infrastructure, distributed training, model serving, inference, performance, MLOps, and platform engineering roles across major US technology markets, built with fresh insights from DeepRec.ai's recent hiring mandates and candidate database.

Read our salary guide here

AI Inference and Serving Model Efficiency

Alongside our broader AI Infrastructure division, DeepRec.ai has a dedicated team focused purely on AI inference and serving efficiency.

As AI systems move from research environments into production, inference becomes the moment of truth. Latency, throughput, cost per request, hardware utilisation, and system reliability all come under pressure at scale. The engineering challenges shift from experimentation to optimisation, from building models to operating them in live, user-facing environments.

Our inference-focused consultants work with teams building high-performance serving systems, real-time and batch inference pipelines, model optimisation frameworks, and accelerator-aware deployment environments. We support organisations hiring engineers who understand quantisation, model compression, distributed inference, GPU scheduling, and system-level efficiency.

If your priority is deploying models reliably and efficiently in production, explore our AI Inference recruitment expertise to see how we support teams operating at this level.

Learn more

Who We Partner With 

We work with organisations building, scaling, and operating AI infrastructure in production, ranging from early-stage teams establishing core platforms to scale-ups expanding distributed systems, and enterprises investing in large-scale AI compute and platform capability.

We also work closely with engineers, researchers, and technical leaders who build and operate AI infrastructure. Many of the people we support are not actively looking for new roles, but are open to conversations about work that is technically meaningful, well-resourced, and aligned with how they want to operate.

Our role is to bring these two sides together thoughtfully, matching organisations with engineers where technical context, expectations, and long-term goals are aligned.

If you're interested in exploring a fulfilling new role in AI infrastructure, learning more about current market trends, or you'd like to hire exceptional talent, our consultants are always available to support you. Please get in touch with us directly, and we'll get back to you as soon as possible: 

Contact the team

MEET THE TEAM

Anthony Kelly

Co-Founder & MD EU/UK

Theodore Faulkner

Business Manager, United States | AI & ML

Sam Warwick

Senior Consultant - ML Systems + AI Infra

Edward Killin

Principal Recruitment Consultant

Luke Weekes

Senior Consultant

Amsterdam, Provincie Noord-Holland, Netherlands
System Performance Architect
Senior Systems Performance Engineer – Embedded TechnologyLocation: Amsterdam, NetherlandsWorking Pattern: Hybrid – 2 days per week in the officeSalary: €100,000 – €140,000 per annum + packageJob Type: PermanentThe OpportunityWe’re working with a global technology organisation developing next-generation systems and connected devices, and they’re looking for a Senior Systems Performance Engineer to join a specialist engineering and research team.This is a highly technical role focused on making complex devices faster, smoother and more power-efficient.You’ll work at the intersection of operating systems, system software and hardware, investigating difficult performance problems and developing solutions that can ultimately be implemented and measured on real devices.This isn't an AI model development role. The focus is on low-level systems performance, operating systems and device optimisation.What You'll Be Working OnDepending on your background, you could be working across areas including:Operating system and kernel performance optimisationCPU scheduling and resource allocationProcessor and core selectionPower and thermal managementDynamic Voltage and Frequency Scaling (DVFS)CPU, GPU and memory performanceSystem profiling and performance analysisApplication responsiveness and latencyGraphics, rendering and frame performanceRuntime and framework optimisationHardware/software performance optimisationPerformance improvements across heterogeneous computing environmentsThe team works on complex problems where improvements need to be measured, validated and demonstrated on real hardware.What You'll Be DoingInvestigating complex system-level performance bottlenecksProfiling systems to understand where processing time and resources are being consumedDesigning and implementing performance improvementsOptimising scheduling and resource allocationWorking with CPU, GPU, memory and other hardware resourcesBalancing performance, power consumption and thermal constraintsImproving application responsiveness and system smoothnessCollaborating closely with hardware, chipset, OS and software engineering teamsResearching new approaches to system performance and evaluating their practical valueTaking ideas from investigation and prototyping through to implementation and measurementContributing technical direction to future performance improvementsYour BackgroundWe're open to different technical backgrounds. You do not need to have experience across every area listed above.We're particularly interested in engineers with strong experience in one or more of the following:Linux Kernel / Android KernelOperating SystemsSystem SoftwareCPU SchedulingPerformance EngineeringPower ManagementThermal ManagementDVFSMemory PerformanceGPU / Graphics PerformanceAndroid FrameworksRuntime OptimisationEmbedded SystemsSoC / Chipset PerformanceRelevant titles could include:Senior, Staff or Principal Systems Engineer, Kernel Engineer, OS Engineer, System Software Engineer, Performance Engineer, Platform Engineer, Android Framework Engineer, Runtime Engineer or Graphics Engineer.Your current job title is less important than the depth and relevance of your technical experience.What We're Looking ForWe're particularly interested in engineers who can demonstrate that they have:Solved complex performance problems at system levelPersonally implemented technical improvementsUsed profiling or performance analysis tools to identify bottlenecksMeasured the impact of their work using metrics such as latency, frame rate, power consumption, memory usage or processing efficiencyWorked closely with hardware or chipset teamsDelivered changes that have been deployed to real devices or embedded platformsStrong programming experience, particularly in C/C++ or other low-level/system programming environmentsA typical strong candidate might come from an OS, kernel, Android, embedded, chipset or device-performance background.Why This Role?This is an opportunity to work on technically challenging problems where your work has a direct impact on real-world device performance.Rather than simply analysing performance issues, you'll have the opportunity to investigate the underlying cause, develop solutions and see those solutions implemented and measured on physical hardware.If you enjoy working close to the operating system, understanding how hardware and software interact, and solving problems that require genuine systems-level engineering, this could be a strong fit.Location & Practical DetailsAmsterdam, NetherlandsHybrid working, with approximately 2 days per week in the officeCandidates already based in the Netherlands or willing to relocate are encouraged to applyStrong spoken and written English requiredCompetitive salary in the region of €100,000–€140,000, depending on experience and overall packageCandidates with relevant notice periods are welcome to applyInterested?If your background is in systems, kernel, operating systems, embedded platforms or device performance, we'd be interested in hearing from you.
Nathan WillsNathan Wills