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.

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Why 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 - SECO & AUG Licensed

As part of Trinnovo Group, DeepRec.ai maintains both SECO and AUG licenses, enabling us to 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: https://www.deeprec.ai/community

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.

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

AI INFRASTRUCTURE CONSULTANTS

Anthony Kelly

Co-Founder & MD EU/UK

Sam Warwick

Senior Consultant - ML Systems + AI Infra

Jacob Graham

Senior Consultant

LATEST JOBS

Massachusetts, United States
BMS AI Edge Software Engineer
BMS & AI Edge Software Engineer Battery Systems | AI for Science | Energy Storage Our client is a publicly listed, AI driven energy technology company operating at the intersection of advanced materials science, battery engineering, and machine learning. Their mission is simple but ambitious: accelerate the global energy transition by using AI to fundamentally change how batteries are designed, validated, and operated. They are pioneers in applying AI directly to battery chemistry, materials discovery, and battery management systems, enabling next generation Li ion and Li metal batteries across transportation, energy storage, robotics, aviation, and defense adjacent applications. The Opportunity Our client’s Energy Storage Systems R&D group is seeking a BMS & AI Edge Software Engineer to design and deploy AI centric State of X (SoX) algorithms that run on edge devices. This role sits squarely between battery physics, embedded software, and applied machine learning. You will own algorithm development from concept through edge deployment, working closely with battery scientists, hardware engineers, and customer facing teams to bring production ready software into real world environments. Key Responsibilities Algorithm R&D for SoXDesign and implement SoX architectures covering charge, health, power, safety, degradation, and related metricsTranslate models and logic into production grade code running on edge devicesCollaborate with battery physicists and engineers on model selection and validationModel Design & OptimizationResearch and evaluate alternative algorithms to improve accuracy, robustness, and performanceOptimize models and software for real world operating constraintsPresent results internally and demonstrate measurable improvementsVerification & DeliveryTest and validate software as a production ready product using defined methodologiesSupport validation at customer sites or manufacturing plants as requiredEngage directly with customers to support deployment and technical approvalRequirements EducationPhD or Master’s in Electrical Engineering, Computer Science, AI, or a closely related fieldEquivalent hands on industry experience will be consideredExperience5 to 9 years of experience in Li ion batteries, BMS, or ESS software engineering (10 years for Senior level)Strong background in BMS sensing and control software including voltage, temperature, current, and diagnosticsSolid understanding of battery chemistries and characteristics such as OCV, C rate behavior, and impedanceExperience developing data driven or AI based algorithms for battery systems, ideally deployed on edge or cloudProven experience coding, integrating, validating, and delivering production softwareExposure to customer facing delivery or deployment projectsPreferred BackgroundBattery characterization methods such as GITT, dQ/dV, or similarPower electronics knowledge including DC/DC or DC/AC conversionFamiliarity with power delivery architectures such as UPS or battery backup systems for data centersWhat’s On OfferHighly competitive base salary and strong benefitsMeaningful equity participation in a publicly listed businessDirect impact on globally relevant energy and sustainability challengesWork alongside leading experts in AI, battery science, and engineeringLong term growth opportunities in a technically serious R&D environment
Sam WarwickSam Warwick