Location: Munich (Hybrid/On-site depending on team setup) Type: Full-time Company Overview We are working with a fast-growing Vision / AI company building production software for the food and retail industry. Their systems help customers reduce food waste and improve operational efficiency - supporting sustainability goals through real-time computer vision and automation. With teams across Europe, the US, and Asia, we combine startup pace with real-world deployments at enterprise customers.The Role We are hiring a hands-on engineer to support the delivery of our computer vision / ML products into production. This role sits at the intersection of software engineering applied machine learning, with a strong focus on making ML models run fast, reliably, and at scale on edge devices. You will be responsible for our core video processing framework and deployment stack, working closely with senior ML engineers to ensure model inference performance, stability, monitoring, and field success. While you won’t be expected to design new ML algorithms or lead model training, you will be involved in diagnosing model issues in the field and improving real-world performance through optimization and iteration.This is a great fit for someone who enjoys real-world ML delivery: video streams, edge devices, inference performance, and production debugging.Key Responsibilities ML Model Runtime & Edge PerformanceMake ML models run efficiently on edge devices (latency, throughput, CPU/GPU utilization, memory constraints)Support inference optimization and troubleshooting (profiling, batching, pipeline tuning, runtime constraints)Investigate real-world model failures (data quality, camera placement, lighting, drift, edge-case behaviour) and work with ML engineers on mitigation strategiesEnsure robust model rollout processes: versioning, validation, safe deployment cyclesVideo Pipeline Engineering (Core Focus)Design and optimize real-time video processing pipelines using GStreamerIntegrate and manage streams from IP cameras (RTSP/ONVIF) and USB camerasDebug complex video stream issues (encoding/decoding, dropped frames, jitter, latency, network instability)Deployment & Production OperationsPackage and deploy services using Docker/Podman on Linux-based edge systemsTroubleshoot issues directly on production/staging Linux hosts (logs, profiling, system-level debugging)Implement and maintain monitoring and device health checks (e.g., Checkmk or similar)Event Streaming & InterfacesBuild interfaces between edge devices and online tools / connected machinesWork with event streaming systems (Kafka or similar) for detections, events, and telemetrydeep Kafka expertise isn’t required, but strong conceptual understanding isMust-Have Skills2–5 years of professional experience in software engineering / applied ML engineeringStrong Python skills (asyncio, threading, multiprocessing)Strong Linux skills: CLI, systemd, bash scripting, networking fundamentalsSolid experience with containerization (Docker or Podman)Comfortable debugging real systems remotely and working end-to-end (not just coding isolated modules)Interest in ML delivery and computer vision systems in productionNice to HaveExperience with GStreamer (big plus)Familiarity with computer vision pipelines (OpenCV, image processing)Experience with FFmpeg, RTSP, H.264/H.265, ONVIFWebRTC exposure (low-latency streaming)Kafka / message broker familiarityGerman language skills (corporate language is English)Why This Role is InterestingYou’ll work at the “real ML” layer: getting models running in production environments where conditions are messyStrong collaboration with senior ML engineers, with room to grow into more ML responsibility over timeDirect ownership of the edge inference video stack powering real customer deploymentsInternational team, low bureaucracy, hands-on culture

Location: Munich (Hybrid) Type: Full-time Company Overview We are working with a fast-growing Vision / AI software company building production-grade computer vision systems for the food and retail sector. Their products help customers reduce food waste, improve operational efficiency, and contribute to sustainability goals by enabling better decision-making through real-time visual intelligence. With an international footprint across Europe, the US, and Asia, they combine startup speed with real-world deployments at large enterprise customers. The Role We are looking for a Senior Machine Learning Engineer to take hands-on technical ownership of a key vision product that is moving into field testing with major retail partners in Germany. This role is ideal for someone who enjoys being deeply involved across the entire ML lifecycle - from model development and training through to deployment on edge devices at customer sites. You will act as a hands-on technical lead for the product, driving model improvements, performance validation, and production rollouts. Key Responsibilities Model DevelopmentDesign, implement, and iterate on deep learning architectures for real-time object tracking and event detectionTrain and optimize object detection models using production datasets and domain-specific video dataContinuously improve model robustness for real-world conditions (lighting changes, occlusions, camera angles, motion blur, etc.)Performance Evaluation & ValidationBuild and execute evaluation workflows for accuracy latency benchmarkingTest models using benchmark video datasets and dedicated hardware setupsMonitor model performance regressions and validate incremental updates before releaseDeployment & Integration (Edge / Production)Own the technical process of deploying model updates into production systemsEnsure stable integration of models into the wider software stack running on-siteSupport field testing cycles, troubleshooting and optimizing performance on edge devicesTooling & PipelinesMaintain and improve internal pipelines for:automated model trainingdata versioningperformance testingreproducible experimentationDrive best practices across model development and deployment workflowsRequirements5–8 years experience in Machine Learning / Deep Learning / Computer VisionStrong proficiency in Python PyTorchHands-on experience training object detection models (e.g., YOLO-style / Faster R-CNN / transformer-based detectors, etc.)Solid software engineering skills in a Linux environmentStrong ownership mindset: able to maintain and advance the full ML stack end-to-endMotivated to learn and apply new methods and improve production qualityMust HaveNative German speaker (customers and field partners are Germany-based)Nice to HaveExperience deploying ML models to edge devices / embedded environmentsFamiliarity with performance profiling / inference optimizationExperience with real-time video pipelines and production CV systemsWhat’s On OfferHybrid working model in MunichFlat hierarchies, high ownership, hands-on cultureInternational, multicultural environment with colleagues across multiple regionsDirect impact on a product entering real-world rollout with major German retailersBenefits/perks including mobility options, company events, and additional corporate benefits

Senior / Principal Research Scientist – Core AI Algorithms (Autonomous Systems)Location: Germany (Remote-first within Germany, on-site in Frankfurt every 2–4 weeks)About the RoleWe are partnering with a global automotive OEM building a core AI research and algorithm team responsible for the foundational intelligence behind next-generation automated driving systems.This role is research-driven and sits upstream of product teams. The focus is on inventing, validating, and transitioning new perception and world-modeling algorithms from research into production-ready systems. The team operates similarly to a big-tech research lab, but with a clear path to real-world deployment.Research Focus AreasDepending on background and interest, you may work on topics such as:3D scene understanding and world modelingOccupancy, motion forecasting, and dynamic scene reconstructionMulti-sensor perception (camera, LiDAR, radar)Representation learning for autonomous systems (BEV, implicit / generative 3D, Gaussian models, foundation models)Robustness, generalization, and long-tail perceptionLearning under weak, sparse, or noisy supervisionBridging offline training with real-world deployment constraintsKey ResponsibilitiesConduct original research in perception and autonomous systems with clear technical ownershipDesign and prototype novel algorithms and learning frameworksPublish at or contribute toward top-tier conferences and journals (e.g., CVPR, ICCV, ECCV, NeurIPS, ICRA, IROS)Translate research ideas into scalable, production-oriented implementationsCollaborate with applied ML, systems, and hardware teams to ensure feasibilityShape the long-term technical roadmap of the core AI organizationMentor junior researchers and engineers where appropriateRequired BackgroundPhD (or equivalent research experience) in Computer Vision, Machine Learning, Robotics, or a related fieldStrong publication record at top-tier conferences or journalsExperience conducting research within an industrial or applied settingExcellent understanding of modern deep learning methods and 3D perceptionStrong programming skills in Python and/or C Ability to work across the full spectrum from theory to implementationStrongly PreferredResearch experience in autonomous driving, robotics, or embodied AIWork on 3D perception, tracking, SLAM, or world modelsExperience at big-tech research labs, industrial AI labs, or advanced OEM R&DFamiliarity with real-world constraints such as runtime, memory, and system integrationPrior collaboration with product or engineering teamsWhat’s on OfferA research-first role with real influence on production systemsThe opportunity to define core algorithms, not just incremental improvementsA team culture that values publications, patents, and long-term thinkingRemote-first working model within Germany, with regular in-person collaboration in FrankfurtCompetitive compensation aligned with senior / principal research profilesWho This Role Is ForResearchers who want their work to ship into real vehiclesIndustry researchers seeking greater technical ownershipPhD-level candidates who enjoy both publishing and buildingProfiles combining academic depth with practical engineering maturityLooking forward to seeing your profile!

Hiring a DevOps Engineer for one of the most exciting deep-tech companies in Europe right now. This is a fixed-term role (until June 2026) based in Zaragoza or Barcelona, with a hybrid setup and real flexibility. You’d be joining a fast-scaling Series B company working at the intersection of quantum computing and AI. The tech is already live in production — compressing large language models by up to 95 percent and cutting inference costs by 50–80 percent. This isn’t theoretical. It’s being used by global enterprises today. Why this role is special You won’t be maintaining legacy systems. You’ll be building, scaling, and optimizing the infrastructure behind cutting-edge AI products used by Fortune 500 clients. You’ll have real ownership and a seat at the table when DevOps strategy decisions are made. What you’ll do • Optimize and scale high-performance inference and internal APIs • Build and improve CI/CD pipelines and automation • Own AWS infrastructure for secure, highly available systems • Work closely with engineers, product teams, and customers • Help deploy software directly into customer environments What we’re looking for • 2–5 years of DevOps experience • Strong AWS and infrastructure-as-code experience • CI/CD expertise (GitLab, GitHub Actions, Jenkins, etc.) • Docker and Kubernetes in production • Solid scripting or coding skills (Python, Bash, Go) • Someone who can troubleshoot fast and communicate clearly What’s on offer • Competitive salary • Signing bonus retention bonus • Hybrid working and flexible hours • Relocation support if needed • Equal pay guaranteed • International, high-impact environment

Location: Europe (strong preference for Spain, ideally Madrid) Type: Full-time About the Company We're working with a high-growth startup developing AI systems that allow industrial robots to perform tasks they currently cannot, starting with complex warehouse operations like mixed palletizing. Their technology combines deep reinforcement learning (DRL) with modern sequence modeling to tackle control and combinatorial optimization problems where classical approaches fail.They are a small, highly skilled team. Joining us means having direct impact, minimal bureaucracy, and ownership over core technology that will be deployed in real-world, high-throughput environments. Role Overview As the second hire in the DRL team, you will own the end-to-end reinforcement learning stack: from problem formulation to algorithm design, large-scale training, evaluation, and deployment. You will work closely with the technical leadership to translate cutting-edge DRL research into practical production throughput at operational sites. This role is highly autonomous, requiring a hands-on expert capable of leading experiments, troubleshooting complex issues, and establishing best practices for algorithm development and deployment. Key ResponsibilitiesDesign, implement, and ship DRL algorithms (e.g., PPO, SAC, DDQN and variants) incorporating advanced architectures such as encoders, cross-attention, and pointer networksOptimize stability and sample efficiency using techniques such as GAE, reward shaping, normalization, entropy/KL control, curriculum learning, and distributional/value-loss tuningSet up and manage large-scale training pipelines: multi-GPU training, parallel rollouts, efficient replay/storage, reproducible experimentsProductionize algorithms with clean, maintainable PyTorch code, profiling, Dockerized services, cloud deployments (AWS), experiment tracking, and dashboardsCollaborate with leadership to align technology with business goals and customer needsMentor and grow future team members, fostering a culture of technical excellence and innovationRequired QualificationsProven track record delivering DRL systems beyond academic demos: led at least one end-to-end DRL system from concept to production or achieved a state-of-the-art benchmark in the last 3–5 yearsDeep expertise in reinforcement learning and deep learning, with strong PyTorch skillsSolid understanding of DRL theory: MDPs, Bellman operators, policy gradients, trust-region/KL methods, λ-returns, stability and regularization in on-policy/off-policy regimesSystems experience: Python, Linux, multi-GPU training, Docker, cloud deployments (AWS preferred)Comfortable taking ownership of experiments, code quality, and results in a small, high-impact teamPhD or equivalent experience in DRL is acceptable; strong academic-only candidates considered if they demonstrate deep expertiseNice to HaveRobotics experience is not requiredProduction system deployment experience is beneficial but not mandatoryLocation & TravelEU-based (CET ±1) with occasional travel to customer sitesPreference for candidates in Spain; otherwise, EuropeCompetitive Compensation & Real Equity Offered.Interview ProcessDeep Technical Session – with CTO, focused on past DRL work (no coding tests, no homework)Traits & Skills Interviews – Two × 1-hour sessions with co-founders to assess problem-solving, communication, and startup fitTeam Meet & Offer – final discussion and reference checkWhy This Role is ExcitingWork at the frontier of DRL robotics in real-world, high-throughput industrial applicationsHigh autonomy, technical ownership, and direct impact on deployed AI systemsSmall, experienced founding team and strong early customer traction reduces commercial risk while maximizing technical challengeOpportunity to join a founding-stage team with equity and influence over core product and technology

We are seeking an experimental physicist with strong hands-on experience in atomic, optical, or quantum systems to help build and operate advanced experimental platforms. You will work directly with precision hardware for qubit control, measurement, and system scaling, contributing to the development of next-generation quantum technologies.This is a lab-focused role for someone who enjoys designing experiments, troubleshooting complex setups, and collaborating across disciplines to turn ideas into working systems. Responsibilities Design, build, and characterize optical, vacuum, and/or cryogenic experimental systemsImplement protocols for qubit preparation, control, and readoutIntegrate lasers, RF/microwave systems, control electronics, and data acquisitionAnalyze experimental data and optimize performance and stabilityTroubleshoot hardware and control issues across the full experimental stackCollaborate with engineers and scientists to inform system design and scalingRequirements Ph.D. in Physics, Applied Physics, Electrical Engineering, or related fieldHands-on experience with experimental quantum systems (AMO, solid-state, or superconducting)Familiarity with qubit control, spectroscopy, or precision measurementStrong experimental problem-solving skillsExperience using Python or similar tools for experiment control and analysisA collaborative mindset and clear communication skills

Senior AI Solutions Engineer – SalesInsurtech | Generative AI | Enterprise InsuranceAbout Our ClientOur client is a Series B–backed AI company transforming the property and casualty insurance industry through applied generative AI and intelligent automation. They work directly with large insurers to modernise core workflows, reduce operational cost, and improve customer experience using production-grade AI agents deployed across claims, policy, and service operations.They are scaling rapidly and are now hiring a senior, customer-facing AI Solutions Engineer to sit at the intersection of sales, product, and deployment.The RoleThis is a high-impact, technical commercial role. You will act as the technical authority throughout the customer lifecycle, from pre-sales through implementation and expansion.You will work closely with sales, customer success, and engineering teams to translate insurer requirements into robust, secure, and scalable AI solutions that deliver measurable business outcomes.This role suits someone comfortable owning conversations with CIO, CTO, and enterprise IT stakeholders while remaining hands-on with architecture, integrations, and demos.What You’ll DoPre-Sales & Technical DiscoveryPartner with sales teams to scope insurer requirements and design AI-driven solutionsPresent system architecture, security posture, and integration approaches to senior technical stakeholdersBuild tailored demos, proofs of concept, and solution prototypes aligned to insurer environmentsSolution Design & ImplementationAssess insurer core platforms including policy administration, claims, and billing systemsDesign and lead integrations across APIs, SSO, and workflow orchestrationSupport and guide deployments to ensure smooth onboarding and production readinessCustomer Advisory & ExpansionAct as a trusted technical advisor for insurer clients adopting AI at scaleIdentify opportunities for expansion across advanced AI agents, workflows, and APIsFeed customer insights back into product and engineering teams to influence roadmap prioritiesThought LeadershipRepresent the business in client workshops, technical sessions, and industry eventsProduce technical documentation, integration guides, and solution playbooks for enterprise customersWhat We’re Looking ForMust Have7–10 years in solutions engineering, pre-sales architecture, or enterprise technical consultingDeep experience within insurance technology ecosystems such as Guidewire, Duck Creek, Majesco, One Inc., Insuresoft, or SapiensStrong hands-on experience with APIs, cloud platforms (AWS, Azure, GCP), and enterprise integrationsProven ability to lead complex, multi-stakeholder enterprise implementationsExcellent communication skills with the ability to explain complex technical concepts to non-technical executivesComfortable operating in a fast-moving, high-ownership startup environmentNice to HaveExposure to AI, ML, automation platforms, or NLP-driven systemsBackground working in high-growth startups or insurtech vendorsFamiliarity with insurance compliance, data security, and regulatory frameworks

Product Developer – GeoAI & Spatial IntelligenceLocation: Europe (hybrid or remote options available)Level: Mid to SeniorAbout our client:Our client is a Swiss-Italian deep-tech company focused on applying machine learning to large-scale spatial data. By combining satellite imagery, mobility data, and crowd-sourced mapping, they deliver actionable intelligence across sectors including urban management, transportation, infrastructure, real estate, insurance, marketing technology, and socio-demographic analysis.They work at the intersection of Earth Observation, AI, and real-world decision-making, helping public and private organisations turn complex geospatial data into practical outcomes.The role:Our client is looking for a Product Developer to help shape the next generation of GeoAI-powered products. This role sits at the boundary between research, engineering, and the market.You will analyse past and ongoing projects, identify where research outputs can be transformed into scalable, market-ready products, and help define the product strategy moving forward. You will also assess market needs across multiple sectors and guide the innovation roadmap accordingly.This is a hands-on, cross-functional role requiring both strategic thinking and practical execution.Key responsibilities:Work closely with data scientists, engineers, researchers, and commercial teams to design and evolve GeoAI products.Translate complex AI, Earth Observation, and urban analytics outputs into clear, user-focused products.Conduct market analysis to identify unmet needs, sector gaps, and high-impact opportunities.Evaluate whether existing capabilities can solve identified problems, and define enhancements where needed.Define new products when market needs are not addressed by current solutions, ensuring feasibility and strategic alignment.Build and maintain a clear product roadmap prioritised by impact, value, and user needs.Gather and interpret feedback from users, clients, and market research to drive continuous improvement.Track product performance post-launch and recommend refinements or new initiatives.Required background:Bachelor’s or Master’s degree in Engineering, Data Science, GIS, Environmental Science, Business, Marketing, Product Management, or a related discipline.5 years of experience in product strategy or product development involving geospatial data.Strong problem-solving ability, with a track record of turning research, technical concepts, and market insight into concrete product plans.Solid understanding of software development lifecycles, data visualisation, and UX/UI principles.Comfortable working in fast-moving, multidisciplinary teams and with external stakeholders.Familiarity with remote sensing or urban analytics is required.Experience with AI, cloud platforms, geospatial tooling, or mapping libraries is a strong advantage.Why this opportunity:Join a fast-growing international deep-tech company operating at the forefront of geospatial AI.Work on real-world problems with tangible impact on cities, infrastructure, and society.Collaborate with leading public and private institutions on globally relevant projects.Flexible working environment with a strong emphasis on learning, creativity, and innovation.