Training Infrastructure Engineer Salary: €80,000 to €150,000 equity Location: Fully remote within Europe (CET ±2 hours) Stage: Recently funded Series A AI startup We are partnering with a fast-growing generative AI company building the next generation of creative tooling. Their platform generates hyper-realistic sound, speech, and music directly from video, effectively bringing silent content to life. The technology is already being used across gaming, video platforms, and creator ecosystems, with a clear ambition to become foundational infrastructure for audio-visual storytelling. Backed by top-tier venture capital and fresh Series A funding, the company is now scaling its core engineering group. This is a chance to join at a point where the technical challenges are deep, the scope is wide, and individual impact is unmistakable. The Role:As a Training Infrastructure Engineer, you will own and evolve the full model training stack. This is a hands-on, systems-level role focused on making large-scale training fast, reliable, and efficient. You will work close to the hardware and close to the models, shaping how cutting-edge generative systems are trained and iterated. What You Will Do:Design and evaluate optimal training strategies including parallelism approaches and precision trade-offs across different model sizes and workloadsProfile, debug, and optimise GPU workloads at single and multi-GPU level, using low-level tooling to understand real hardware behaviourImprove the entire training pipeline end to end, from data storage and loading through distributed training, checkpointing, and loggingBuild scalable systems for experiment tracking, model and data versioning, and training insightsDesign, deploy, and maintain large-scale training clusters orchestrated with SLURMWhat We Are Looking For:Proven experience optimising training and inference workloads through hands-on implementation, not just theoryDeep understanding of GPU memory hierarchy and compute constraints, including the gap between theoretical and practical performanceStrong intuition for memory-bound vs compute-bound workloads and how to optimise for eachExpertise in efficient attention mechanisms and how their performance characteristics change at scaleNice to Have:Experience writing custom GPU kernels and integrating them into PyTorchBackground working with diffusion or autoregressive modelsFamiliarity with high-performance storage systems such as VAST or large-scale object storageExperience managing SLURM clusters in production environmentsWhy This Role:Join at a pivotal growth stage with fresh funding and strong momentumGenuine ownership and autonomy from day one, with direct influence over technical directionCompetitive salary and equity so you share in the upside you help createWork on technology that is redefining how creators produce and experience contentIf you want to operate at the intersection of deep systems engineering and frontier generative AI, this is one of the strongest opportunities in the European market right now.

AI Engineer (Infrastructure) – London -Hybrid, £85k Stock Options Are you ready to help world-leading enterprises deploy cutting-edge AI at scale? We’re looking for an AI Infrastructure Engineer to join a pioneering AI company that’s transforming the way businesses operate. This isn’t just AI - it’s agentic AI that can drive decisions, optimize workflows, and unlock insights that were previously impossible. Trusted by Fortune 500 clients across finance, healthcare, and enterprise, this company has grown 500% year-on-year since emerging from stealth mode in 2021, backed by over $50M from top-tier investors and visionary angels. The Role You’ll be the bridge between enterprise infrastructure and AI innovation. Your focus will be on deploying advanced AI solutions into complex client environments, ensuring reliability, security, and scalability. Your expertise will determine how seamlessly it integrates into real-world systems. What You’ll DoCollaborate with top-tier enterprise clients to design and deploy bespoke AI workflows.Build robust architectures leveraging the latest AI technologies, including LLMs, RAGs, MCPs, and agentic workflows.Ensure enterprise-grade deployment across cloud and on-prem environments, with focus on availability, observability, and security.Translate complex business challenges into scalable, intelligent AI solutions.Serve as a forward-deployed engineer, working closely with both technical teams and business stakeholders.What You’ll BringProven experience deploying enterprise-grade AI or machine learning solutions in cloud and/or on-premise environments.Hands-on familiarity with at least one major cloud provider and strong DevOps skills.Client-facing experience with the ability to design, deliver, and support production-grade AI solutions.Strong solution architecture skills and a track record of driving measurable impact.Bonus points for personal AI projects or agentic AI experience.Why This Role Is ExcitingWork on high-visibility projects that truly change how enterprises operate.Join a company backed by world-class investors and trusted by global Fortune 500 clients.Be part of a team where 50% of members are PhDs, selected from over 50,000 applicants.Enjoy a collaborative, hybrid work environment (office Tues & Weds, optional additional days).BenefitsCompetitive salary (flexible for exceptional candidates)Share options and pension scheme25 days’ paid holiday plus bank holidays (carry over/sell up to 5 days)Work abroad days and flexible benefits, including Health/Dental InsuranceLearning & development budget, tech purchase support, office snacks, team events, referral bonusesInterview ProcessInitial screening callHiring manager/team interview (30-45 mins)Take-home challenge (3 hrs)In office interview - Speak with 3 members of the team (30 mins each), then a final chat with foundersThis is your chance to join a company that’s shaping the future of AI in enterprise. If you thrive in a high-impact environment where your work directly drives client success, this role is for you.

AI Engineer / GenAI Engineer / Data Scientist Location: Bratislava (preferred) or wider Europe (Iberia / Eastern Europe) Contract: Freelance / Day Rate Rate: 450 - 600 Euros per day  Start Date: ASAP A leading European organisation is expanding its GenAI capability within the asset management domain and is seeking an experienced AI Engineer / GenAI Engineer / Data Scientist. You will join a fast-moving, delivery-focused team that has spent the last two years developing high-impact GenAI use cases. Now entering the next phase of scaling and refinement, the team is looking for someone who can take ownership, build robust solutions, and strongly influence technical direction. You will be working on advanced AI systems built on Palantir Foundry and AIP, including two live solutions supporting portfolio managers.This is a hands-on engineering position where you will work closely with data scientists, ML engineers, and functional teams across the organisation. Key ResponsibilitiesDesign, build, and enhance GenAI / LLM-powered solutionsDevelop agents, prompts, and content extraction / summarisation pipelinesImplement and optimise RAG architectures within Palantir Foundry AIPDefine and build evaluation frameworks to validate model outputsEnsure data structures and pipelines support scalable GenAI use casesCollaborate with cross-functional teams (approx. 12 people across 3 teams)Contribute to solution design, experimentation, and productionisationAdvocate for best practices across AI engineering and model evaluationEssential Skills & ExperienceStrong background in GenAI, LLMs, and applied data scienceHands-on experience with:LLM-based content extractionSummarisation workflowsPrompt engineeringAgent designRAG pipelinesExperience with Palantir Foundry and AIP Ability to validate outputs and build evaluation frameworksComfortable working in small, agile engineering teamsStrong communication skills and ability to work cross-functionally

Machine Learning Engineer (NLP) About the Company This early-stage environmental intelligence startup is building next-generation AI systems that help global organisations understand and plan for water-related risks. Their platform combines deep learning with physics-based modelling to generate high-resolution insights for some of the world’s largest infrastructure operators, consumer brands, and investors. Backed by leading scientific minds across climate, hydrology, and machine learning, the company is now expanding its capabilities by developing a new social risk function that captures the human, regulatory, and community dynamics that shape water outcomes around the world.Why JoinJoin a team pushing the boundaries of environmental intelligence, combining physical and social risk modelling into a unified AI platform. Work with world-class researchers, publish meaningful science, and help deliver tools with tangible global impact.Pioneer a new capability: You’ll be the first ML engineer dedicated to modelling social, political, and reputational water risk.Cutting-edge work: Blend NLP, LLMs, graph intelligence, and geospatial modelling into a real, production platform.Genuine impact: Your models will inform global water stewardship decisions across high-risk regions.Interdisciplinary collaboration: Work alongside scientists and researchers across climate, hydrology, and social systems.Early-stage ownership: Build from first principles in a fast-moving, mission-driven startup with strong early traction.What You’ll DoBuild NLP, LLM, and multi-modal pipelines to analyse community, regulatory, media, and public-sentiment signals — including stance detection, topic/event clustering, and stakeholder network mapping.Fuse unstructured social data with geospatial and physical-risk datasets to generate unified risk insights for real-world decision-making.Partner with climate and domain scientists to translate social signals into actionable risk metrics, contributing to both product development and peer-reviewed research.Deploy scalable, interpretable ML systems into production via APIs and platform infrastructure.What You Bring3 years building applied ML/NLP systems, ideally across text, geospatial, or social-network data, including sentiment/stance modelling and multi-source pipelines.Strong Python plus experience with PyTorch/TensorFlow, SQL, and modern LLM tooling (Hugging Face, LangChain, OpenAI APIs).Skilled with entity extraction, topic modelling, network/graph analysis, and data sourcing or weak supervision in multilingual environments.Passion for climate, water, or environmental risk, and comfortable working in an early-stage, collaborative, low-ego environment.Nice to HavePhD / Postdoc with track record of pace and quality of publicationsGraph ML experience or multi-modal fusion (text geospatial).LLM fine-tuning for domain-specific tasks.Deployment experience with FastAPI, Docker, or similar frameworks.Background or exposure to environmental science, hydrology, or social-data analysis.

AI Low-Code Architect (Contract, EU/CH) Location: Europe or Switzerland Workload: 100% Start: ASAP Seniority: Senior / PrincipalLength: 6 months Role Overview We are looking for a highly technical AI Low-Code Architect to support a large enterprise in evolving its automation and AI ecosystem. The position focuses on designing the platform setup, ensuring the right governance structures are in place, and guiding teams on how to build scalable AI and low-code solutions using Power Platform, Copilot Studio, and Azure AI. Key Responsibilities: • Define the technical setup for the organisation’s AI and low-code landscape, covering environments, integration points, and platform configuration. • Shape the security and identity model for the platform, ensuring safe access and consistent governance. • Set standards for how solutions should be designed, deployed, and maintained across Power Platform and Azure. • Lead technical working sessions with architecture, engineering, and security stakeholders. • Provide direction to development teams on how to structure apps, flows, connectors, and AI components. • Create clear architectural documentation to support delivery teams and future enhancements. • Advise on feasibility, technical risks, and overall solution approach for new initiatives. Required Experience • 6–10 years in cloud or Microsoft-focused architecture roles. • Deep understanding of Power Platform architecture (Dataverse, environments, solution structure, ALM). • Strong hands-on exposure to Copilot Studio, Azure OpenAI, Cognitive Search, Logic Apps, and Functions. • Solid grasp of enterprise identity, RBAC, and secure integration practices. • Fluent English. Nice to Have • Experience in large or regulated enterprise environments. • Knowledge of multi-agent AI patterns or Azure AI Foundry.

Project Manager – AI & Low-Code (Contract – 6 Months, Remote EU, Start ASAP) We’re looking for an experienced Project Manager to drive a Europe-wide AI & Low-Code program for a global enterprise client. This fully remote 6-month contract is ideal for someone who thrives on coordinating multiple teams, keeping projects on track, and delivering results in fast-paced environments. What you’ll do:Plan, track, and oversee delivery across multiple squads and countriesCoordinate developers, architects, secuirty and data teams Run agile ceremonies, manage dependencies, and resolve blockersProduce reports, dashboards, and updates for stakeholders and steering committeesSupport testing, go-live, and post-launch activitiesWhat we’re looking for:5–10 years’ experience managing IT or digital transformation projectsFamiliarity with conversational AI deliveryManaging distributed teams and international stakeholdersFluent in EnglishNice to have:PMP, Prince2, or Scrum certificationExperience with enterprise AI programs or Microsoft CoEDetails:Start: ASAPDuration: 6 monthsLocation: Remote (EU-based is a must)Rate: €400–500/day depending on experience

Role: Full Stack Robotics EngineerSalary: upto $250,000Location: San Francisco, CA Opportunity to work on next-generation AI-driven physical systems capable of general-purpose manipulation, experimentation, and manufacturing. I’m looking for several Full-Stack Robotics Engineer to architect, prototype, and harden high-precision electromechanical platforms. You’ll own subsystems end-to-end across motion planning, real-time control, sensing, actuation, mechanical design, and embedded firmware. This role is deeply hands-on and requires first-principles thinking, rapid iteration, and the ability to integrate across disciplines to deliver reliable, high-performance robotic capability. Responsibilities:Build and integrate motion planning, kinematics, control, and perception into robust robotic behaviors.Develop real-time control loops, actuator interfaces, embedded firmware, and system-level safety.Lead mechanical design of end-effectors, precision mechanisms, and structural components.Design electrical systems including sensing, power, actuation electronics, and data pathways.Prototype, validate, and iterate complete robotic stacks from fabrication to deployment.Work cross-functionally to align mechanical, electrical, firmware, and control architecture. Qualifications:Deep expertise in robotics, motion, and real-time control of complex electromechanical systems.Proven experience taking platforms from prototype to reliable operation.Strong mechanical, electrical, and firmware engineering skills.Builder mindset with a drive for quality and novel capability creation.

Role: Senior Digital Twin ML EngineerSalary: upto $250,000Location: San Francisco, CA Work on advanced AI-driven physical systems with broad manipulation and experimental capability. I’m seeking a Senior Digital Twin ML Engineer to build high-fidelity digital twins of robotic, electromechanical, and experimental platforms. You will design model-identification pipelines, calibration routines, dynamic-model learning systems, and multi-scale physics representations that support accurate predictive simulation and closed-loop interaction with RL, planning, and control stacks. This role blends physics intuition, ML modeling, and hands-on experimentation to ensure digital twins remain stable, accurate, and continuously updated as real systems evolve. Responsibilities:Build model-identification and parameter-estimation pipelines with adaptive calibration.Develop ML-based dynamic models, multi-scale physics approximators, and hybrid simulation frameworks.Maintain twin fidelity, stability, and version consistency as data and hardware change.Work closely with simulation, RL, controls, and agent teams to integrate twins into decision-making and learning workflows. Qualifications:Strong experience creating or calibrating digital twins or dynamic, data-driven physics models.Knowledge of system identification, time-series modeling, and physical parameter estimation.Ability to combine physics, ML, and experimental data into robust predictive models.Comfort operating across ML, simulation tooling, and physical hardware interfaces in a fast-paced environment.