(junior) fullstack engineer (m/f/d) for a new product

ai engineer (m/f/d)

data engineer

machine learning engineer

ai & analytics engineer

ai enablement engineer

computer vision engineer

Stealth Startup (Deep Defense Tech)

<div>
 
 
 Senior Computer Vision Engineer
 
 
 
 (Aerial Threat Detection, Classification &amp; Tracking)
 
 
 Location: Berlin (Onsite)
 
 
 
 
 
 
 About Us
 
 
 
 We are a defense technology startup based in Berlin, building the next generation defense layer against aerial threats. Our team develops mission-critical systems that combine hardware, software, sensing, and real-time AI to operate reliably in complex real-world environments.
 
 
 Operating in stealth mode, we place strong emphasis on engineering rigor, real-world performance, and defense-grade system reliability.
 
 
 
 
 
 
 Role Overview
 
 
 
 We are seeking a Senior Computer Vision Engineer to design, train, deploy, and continuously improve computer vision models for aerial threat detection, classification, and tracking.
 
 
 This role focuses on real-world vision challenges: detecting small objects at long range, maintaining tracking stability under poor visibility and motion, classifying targets reliably, and deploying performant models on edge compute platforms such as NVIDIA Jetson / Tegra.
 
 
 You will own key parts of the vision model lifecycle, from dataset preparation and augmentation to model development, deployment optimization, field-data error analysis, and iterative improvement. You will work closely with robotics, tracking, and controls engineers to ensure visual perception outputs can be used reliably in real-time system behavior.
 
 
 This is a hands-on, production-oriented role for someone with deep experience building vision systems that work outside controlled lab conditions.
 
 
 This position requires onsite work in Berlin and candidates must be from a NATO member state.
 
 
 
 
 
 
 Key Responsibilities
 
 
 
 
 
 
 
 Computer Vision Model Development
 
 
 <ul>
 <li>
 Design, train, fine-tune, and deploy computer vision models for: Long-range small-object detection, Object classification and identification, Multi-object tracking, Target state estimation support
 </li>
 <li>
 Work with modern vision approaches, including real-time detectors, CNN-based architectures, vision transformers, tracking-by-detection pipelines, or custom models
 </li>
 <li>
 Evaluate trade-offs between detection accuracy, latency, robustness, and compute constraints
 </li>
 <li>
 Develop model pipelines that support continuous improvement from real-world field data
 </li>
 </ul>
 
 
 
 
 
 Real-World Robustness
 
 
 <ul>
 <li>
 Improve model performance under challenging operating conditions, including: Small targets at long range, Motion blur, Low light, glare, and changing illumination, Clouds, rain, fog, and atmospheric effects, Cluttered backgrounds, Camera movement and vibration, IR / thermal imagery artifacts
 </li>
 <li>
 Analyze failure cases and translate them into concrete model, data, and preprocessing improvements
 </li>
 <li>
 Improve classification confidence, tracking stability, and robustness against false positives#
 </li>
 </ul>
 
 
 
 
 
 Dataset Lifecycle &amp; Synthetic Data
 
 
 <ul>
 <li>
 Own key parts of the vision data pipeline, including: Data cleaning, Augmentation strategies, Label quality analysis, Error analysis, Continuous dataset improvement
 </li>
 <li>
 Use synthetic data to improve coverage of rare, difficult, or safety-critical scenarios
 </li>
 <li>
 Collaborate with simulation engineers to align synthetic data generation with real-world failure cases
 </li>
 <li>
 Define metrics and evaluation sets for long-range detection, classification, and tracking performance
 </li>
 </ul>
 
 
 
 
 
 Tracking &amp; Sensor Fusion
 
 
 <ul>
 <li>
 Develop and improve tracking-by-detection and multi-object tracking pipelines
 </li>
 <li>
 Integrate vision outputs into downstream tracking and control systems
 </li>
 <li>
 Work with sensor inputs including: IR / thermal cameras, Laser range finder data
 </li>
 <li>
 Contribute to sensor fusion approaches where visual detections must be combined with additional measurement sources
 </li>
 <li>
 Collaborate with robotics, tracking, and controls engineers to ensure perception outputs are stable, timely, and actionable
 </li>
 </ul>
 
 
 
 
 
 Edge Deployment &amp; Optimization
 
 
 <ul>
 <li>
 Deploy and optimize models on NVIDIA Jetson / Tegra platforms
 </li>
 <li>
 Optimize inference performance using: TensorRT, CUDA
 </li>
 <li>
 Efficient preprocessing pipelines
 </li>
 <li>
 Balance accuracy, latency, memory usage, and thermal constraints
 </li>
 <li>
 Support real-time perception pipelines running on embedded or edge compute hardware
 </li>
 </ul>
 
 
 
 
 
 Required Qualifications
 
 
 <ul>
 <li>
 6+ years of experience in computer vision, applied machine learning, or real-world perception systems
 </li>
 <li>
 Proven hands-on experience building, training, deploying, and maintaining computer vision models
 </li>
 <li>
 Strong experience with object detection, classification, and/or multi-object tracking
 </li>
 <li>
 Experience with real-world image data, including noisy labels, domain shift, sensor artifacts, and difficult edge cases
 </li>
 <li>
 Strong Python skills and experience with deep learning frameworks such as PyTorch or TensorFlow
 </li>
 <li>
 Experience optimizing and deploying models on edge platforms, ideally NVIDIA Jetson / Tegra
 </li>
 <li>
 Experience with inference optimization tools such as TensorRT and/or CUDA
 </li>
 <li>
 Strong analytical skills for error analysis, model evaluation, and performance debugging
 </li>
 <li>
 Ability to work closely with robotics, controls, and systems engineers
 </li>
 <li>
 Onsite availability in Berlin
 </li>
 <li>
 Citizenship of a NATO member state
 </li>
 </ul>
 
 
 
 
 
 Preferred Qualifications
 
 
 <ul>
 <li>
 Background in defense, aerospace, robotics, autonomous systems, or industrial perception
 </li>
 <li>
 Experience with IR / thermal computer vision
 </li>
 <li>
 Experience with long-range small-object detection
 </li>
 <li>
 Experience with sensor fusion involving visual detections and range measurements
 </li>
 <li>
 Experience with synthetic data generation and simulation-driven dataset improvement
 </li>
 <li>
 Experience with tracking filters, tracking-by-detection, or real-time perception-to-control pipelines
 </li>
 <li>
 Strong C++ skills for production integration are a plus
 </li>
 </ul>
 
 
 
 
 
 What We Offer
 
 
 <ul>
 <li>
 Competitive salary
 </li>
 <li>
 VSOP / equity participation
 </li>
 <li>
 Central Berlin office
 </li>
 <li>
 Extreme growth opportunity in a fast-scaling startup
 </li>
 <li>
 Holiday allowance
 </li>
 <li>
 Monthly voucher
 </li>
 <li>
 Public transportation subsidies
 </li>
 </ul>
 
 
 
 
 
 Who You Are
 
 
 <ul>
 <li>
 Real-world focused: You care about models that work in the field, not just on benchmark datasets
 </li>
 <li>
 Data-driven: You analyze failures systematically and improve models through evidence
 </li>
 <li>
 Performance-aware: You understand latency, memory, and edge deployment constraints
 </li>
 <li>
 Robustness-oriented: You think deeply about edge cases, domain shift, and degraded conditions
 </li>
 <li>
 Collaborative: You work effectively with robotics, tracking, and controls engineers
 </li>
 <li>
 Mission-aligned: You understand the responsibility of building perception systems for defense applications
 </li>
 </ul>
 
 
 
</div>

Senior Computer Vision Engineer

ALMETRA

<div>We&rsquo;re looking for a Computer Vision Engineer focused on bringing advanced vision models into production. You&rsquo;ll own the full lifecycle of CV systems &mdash; from model integration and orchestration to deployment on cloud and edge environments.<h2 class="jobSectionHeader"> 
Your role</h2><ul><li>
Develop and deploy computer vision models for real-world video and sensor applications</li><li>
Build reliable training, evaluation and inference pipelines for large-scale data</li><li>
Operate and optimise GPU clusters, Docker/Kubernetes environments and cloud workloads</li><li>
Implement CI/CD, versioning and orchestration for ML pipelines</li><li>
Collaborate with research engineers to transition prototypes into scalable, production-grade systems</li><li>
Work with robotics and platform teams to ensure robust deployment at the edge</li></ul><h2 class="jobSectionHeader">
You are</h2><ul><li>
5&ndash;7 years experience in computer vision, ML engineering or production AI systems</li><li>
Strong in Python, PyTorch and modern CV architectures (e.g. temporal transformers, detection, tracking)</li><li>
Experienced with containerisation and orchestration (Docker, Kubernetes, MLFlow, Airflow, etc.)</li><li>
Familiar with distributed training, GPU management and inference optimisation</li><li>
Solid understanding of cloud infrastructure (AWS or similar) and MLOps tooling</li><li>
Pragmatic engineer &mdash; focused on reliability, reproducibility and maintainability</li></ul><h2 class="jobSectionHeader">
Nice to have</h2><ul><li>
Experience deploying CV models on edge devices or embedded systems</li><li>
Familiarity with TensorRT, quantisation, and real-time inference optimisation</li><li>
Background in video analytics, action recognition or multi-modal perception</li><li>
Understanding of model orchestration frameworks and large data pipelines</li></ul><h2 class="jobSectionHeader"> 
Why this role matters</h2> 
You bridge research and production &mdash; turning cutting-edge computer vision models into robust, real-time systems that power intelligent industrial automation.
What we offer
Employee Share Options Program for all permanent employees*
An increasing benefits list: currently includes Urban Sports club and quarterly team retreats.
Be on the forefront in defining what artificial intelligence means in manufacturing
Gain hands-on experience in working in an AI-first software company
Supportive and inclusive culture that values diversity and promotes the advancement of underrepresented groups within the company
Collaborate with a diverse (currently more than 10 nationalities) and talented team, working on cutting-edge projects with real-world impact
Network with professionals and leaders in the field, opening doors to potential future career opportunities
We have a very flat hierarchy, open 360&deg; feedback, and flexible working hours
Ethics: We are committed to developing ethical AI software 
 
Don't meet all the requirements?
Almetra is committed to creating a workplace that is diverse, fair, and inclusive. We encourage candidates from all backgrounds, even if they do not meet every qualification, to submit their application. We firmly believe that having a team with diverse perspectives only strengthens our company and drives innovation. Our commitment also extends to providing an accessible environment for everyone, including those with disabilities. Please let us know if you require any accommodations during the application process or while working with us, and we will do our best to support you.<ul><li> 
Only full-time, permanent roles are eligible for stock options. Part-time roles, contract roles, work-student, internships and freelance roles are not eligible for stock options.</li></ul>
Compensation Range: &euro;80K - &euro;120K</div>

Senior Computer Vision Engineer (m/f/d)

Code Compass 🧭

<div>
 
 🤖 Machine Learning Engineer &ndash; Computer Vision &amp; Generative AI &ndash; 100%
 
 
 
 
 
 📍 Berlin, Germany | 💰 &euro;50,000 - &euro;70,000 + Benefits | 🌍 Hybrid Working
 
 
 
 
 
 Our client is a technology-driven organisation developing intelligent software solutions that leverage artificial intelligence, automation, and advanced data processing to solve complex business challenges at scale.
 
 
 
 
 
 Operating at the intersection of machine learning, software engineering, and product innovation, they are investing heavily in next-generation AI capabilities and expanding their engineering team to support the continued evolution of their platform and services.
 
 
 
 
 
 This role is ideal for a Machine Learning Engineer who enjoys taking cutting-edge AI solutions from research to production and wants to work on technically challenging projects with tangible real-world impact.
 
 
 
 
 
 ⚙️ Tech Stack:
 
 
 Python, PyTorch, TensorFlow, Computer Vision, Generative AI, Diffusion Models, GANs, Image Processing, Machine Learning, Docker, Cloud Platforms, Production ML Systems, Automation, AI Workflows
 
 
 
 
 
 🚀 About the Role:
 
 
 
 
 <ul>
 <li>
 As a Machine Learning Engineer, you will:
 </li>
 <li>
 Develop, train, and optimise machine learning models focused on computer vision and generative AI applications
 </li>
 <li>
 Build and deploy scalable ML solutions into production environments
 </li>
 <li>
 Design automation solutions that reduce manual effort and improve operational efficiency
 </li>
 <li>
 Monitor model performance, identify improvement opportunities, and enhance reliability and accuracy
 </li>
 <li>
 Collaborate closely with engineering, product, and operational teams to deliver practical AI-driven solutions
 </li>
 <li>
 Research emerging technologies and rapidly evaluate their suitability for business applications
 </li>
 <li>
 Contribute to the evolution of production-grade machine learning infrastructure and workflows
 </li>
 </ul>
 
 
 
 
 ➕ Nice to Have:
 
 
 
 
 <ul>
 <li>
 Several years of hands-on experience within machine learning and computer vision
 </li>
 <li>
 Strong Python development skills with experience using frameworks such as PyTorch or TensorFlow
 </li>
 <li>
 Practical experience working with generative AI technologies including diffusion models and GANs
 </li>
 <li>
 Understanding of ML deployment, scalability, performance optimisation, and production environments
 </li>
 <li>
 Experience with Docker and cloud-based infrastructure
 </li>
 <li>
 Knowledge of creative AI tools and visual content workflows
 </li>
 <li>
 Experience working with image-based products, digital content platforms, or related industries
 </li>
 <li>
 Strong analytical thinking combined with a pragmatic, solution-oriented mindset
 </li>
 <li>
 Ability to communicate effectively in an international and cross-functional environment
 </li>
 </ul>
 
 
 
 
 💪 Benefits:
 
 
 
 
 <ul>
 <li>
 Opportunity to work on cutting-edge AI and machine learning technologies
 </li>
 <li>
 Highly collaborative and innovative working environment
 </li>
 <li>
 Flexible working arrangements with hybrid options
 </li>
 <li>
 Exposure to challenging technical problems with real-world impact
 </li>
 <li>
 Professional development support, training, and continuous learning opportunities
 </li>
 <li>
 Modern working environment with strong team culture and regular social activities
 </li>
 </ul>
 
 
 
 
 
 ✉️ Due to the volume of applications, we may not be able to respond to everyone individually. However, we genuinely appreciate every application and will contact shortlisted candidates directly.
 
 
</div>

Machine Learning Engineer

<div>We&rsquo;re looking for a Research Engineer to push the limits of vision-language models for real-world video understanding. You&rsquo;ll work on applied, state-of-the-art multimodal models and turn them into production pipelines used by customers.<h3 class="jobSectionHeader">
Your role</h3><ul><li>
Design and adapt vision-language and video models for scene understanding, temporal reasoning and activity / action recognition</li><li>
Build and maintain large-scale training and evaluation pipelines on GPU clusters</li><li>
Curate and augment video-text and action datasets, including synthetic labels and retrieval-based augmentation</li><li>
Develop robust benchmarks for video QA, instruction following and temporal understanding, and use them to drive iterative model improvements</li><li>
Cut and refactor model architectures for efficiency and deployability (compression, pruning, distillation)</li><li>
Deliver production-ready inference pipelines to product and customer teams, working closely with CV, platform and robotics engineers</li></ul><h3 class="jobSectionHeader">
You bring</h3><ul><li>
Completed PhD (or equivalent research track record) in computer vision, machine learning, robotics or a related field</li><li>
Strong background in video-centric deep learning: scene understanding, temporal / activity / action recognition, or video generation</li><li>
Experience training and adapting large vision or VLM models (e.g. InternVL, Qwen-VL, DeepSeek-VL, similar stacks)</li><li>
Proven work with multi-GPU training (PyTorch, distributed, mixed precision) and large-scale datasets</li><li>
Solid engineering habits: clean Python, reproducible experiments, reliable data and training pipelines</li><li>
Track record of moving research into usable systems (demos, internal tools, or productised features) in fast-moving teams</li></ul><h3 class="jobSectionHeader">
Nice to have</h3><ul><li>
Publications at top-tier venues (CVPR, ICCV, ECCV, NeurIPS, ICLR, etc.) on video, multimodal learning or scene understanding</li><li>
Experience with 3D/4D scene representations, action generation or embodied / sense-plan-act style projects</li><li>
Inference optimisation: quantisation, TensorRT, model distillation, or deployment on constrained hardware</li><li>
Prior experience in a startup or applied research lab environment</li></ul>
What we offer
Employee Share Options Program for all permanent employees*
An increasing benefits list: currently includes Urban Sports club and quarterly team retreats.
Be on the forefront in defining what artificial intelligence means in manufacturing
Gain hands-on experience in working in an AI-first software company
Supportive and inclusive culture that values diversity and promotes the advancement of underrepresented groups within the company
Collaborate with a diverse (currently more than 10 nationalities) and talented team, working on cutting-edge projects with real-world impact
Network with professionals and leaders in the field, opening doors to potential future career opportunities
We have a very flat hierarchy, open 360&deg; feedback, and flexible working hours
Ethics: We are committed to developing ethical AI software 
 
Don't meet all the requirements?
Almetra is committed to creating a workplace that is diverse, fair, and inclusive. We encourage candidates from all backgrounds, even if they do not meet every qualification, to submit their application. We firmly believe that having a team with diverse perspectives only strengthens our company and drives innovation. Our commitment also extends to providing an accessible environment for everyone, including those with disabilities. Please let us know if you require any accommodations during the application process or while working with us, and we will do our best to support you.<ul><li> 
Only full-time, permanent roles are eligible for stock options. Part-time roles, contract roles, work-student, internships and freelance roles are not eligible for stock options.</li></ul></div>

VLM Research Engineer (m/f/d)

The Formula

<div>Deine Benefits:<div><ul><li> 
Du arbeitest mit modernsten Technologien.</li><li>
Du wirst Teil eines Teams aus technikbegeisterten Engineers.</li><li>
Du begleitest das n&auml;chste Tech-Unicorn im Verteidigungssektor bei der Entwicklung eines der ersten multinationalen Drohnen-Fr&uuml;hwarnsysteme.</li><li>
Dich erwartet ein multinationales, pragmatisches Hands-on-Team mit starkem Innovationsfokus.</li><li>
Arbeite im B&uuml;ro in Berlin oder M&uuml;nchen &ndash; oder komplett im Homeoffice von &uuml;berall in der EU.</li><li>
Abgesehen von einigen Meetings arbeitest du dann, wann es f&uuml;r dich am besten passt.</li><li>
30 Tage Urlaub.</li><li>
Krankenversicherungspaket.</li></ul></div><div>
Deine Aufgaben:</div><div>
Du wirst Teil eines 35-k&ouml;pfigen Teams aus technikbegeisterten Sensorik-, IoT- und Hardware-Engineers. Gemeinsam mit deinen Kolleginnen und Kollegen &uuml;bernimmst du folgende Aufgaben:</div><div><ul><li>
Du bist Teil des Teams, das ein Ortungsprodukt der n&auml;chsten Generation mit lernender Kartenarchitektur baut.</li><li>
Du entwickelst Computer Vision Models (Dataset Preparation, Auto-Labeling, Training Optimization, Edge/Cloud Deployment) und implementierst die visuellen und akustischen Sensordaten in das System.</li><li>
Du verarbeitest multi-modale Sensordaten (Bilder, Radar, Akustik) unter schwierigen Feldbedingungen wie Jamming oder Sensor-Degradation.</li><li>
Du l&auml;sst Machine-Learning- und KI-Modelle direkt auf den lokalen Sensoren statt auf Cloud-Servern laufen und trainierst die Modellen direkt auf der Edge-Hardware (z. B. NVIDIA Jetson).</li><li>
Du implementierst skalierbare Modelle f&uuml;r Low-Latency-Anwendungen.</li><li>
Du kombinierst GPU-accelerated Vision Models (CUDA, TensorRT, DeepStream) mit skalierbaren backend services.</li><li>
Du arbeitest an real-time Networking von highly scalable Distributed Systems.</li><li>
Gemeinsam mit den Sensor Fusion Engineers, MLOps und DevOps Engineers erm&ouml;glichst du schnelle und sichere Deployments.</li><li>
Du &uuml;berwachst die Systeme, behebst St&ouml;rungen und verbesserst kontinuierlich die Observability.</li><li>
Wenn du m&ouml;chtest, unterst&uuml;tzt du Eins&auml;tze vor Ort, sammelst Sensordaten und validierst die Technologie in kontrollierten Feldversuchen.</li></ul> 
Dein Profil:</div><div><ul><li>
Aufgrund von Sicherheitsbestimmungen f&uuml;r diese Rolle ist die Staatsb&uuml;rgerschaft eines EU-Mitgliedstaates Voraussetzung.</li><li>
Du bist offiziell in einem EU-Land gemeldet.</li><li>
Mindestens 5 (ideal 10-15) Jahre Berufserfahrung im IT-Bereich (z. B. Software Engineering).</li><li>
Mindestens 2 (ideal 4-6)Jahre Vollzeit-Berufserfahrung als Machine Learning Engineer, idealerweise im Bereich Akustik.</li><li>
Mindestens 2 Jahre Berufserfahrung im IoT-Bereich.</li><li>
Flie&szlig;ende Kenntnisse in Python und den relevanten Frameworks.</li><li>
Gute Erfahrung mit dem Embedded-Linux-&Ouml;kosystem.</li><li>
Erste Cloud-Erfahrung.</li><li>
Du hast mindestens 2 Jahre am St&uuml;ck f&uuml;r denselben Arbeitgeber gearbeitet.</li><li>
Flie&szlig;endes Englisch; jede weitere gesprochene Sprache ist ein Plus.</li><li>
Du arbeitest gerne im Verteidigungssektor (Defense).</li><li>
Du bl&uuml;hst in einem dynamischen Startup- bzw. Scaleup-Umfeld auf.</li><li>
Du bist motiviert, f&uuml;r die n&auml;chsten 3-5 Jahre ausschlie&szlig;lich operativ und hands-on (nicht im Management) zu arbeiten.</li><li>
Idealerweise Erfahrung mit Flottendaten (Fleet Data), Bash, Golang, C/C++, MLOps, DevOps.</li><li>
Idealerweise hast du Lust, f&uuml;r 2&ndash;3 Tage pro Monat zu Feldversuchen zu reisen.</li><li>
Du bist mit folgenden Buzzwords vertraut: #MachineLearning #EdgeAI #TinyML #SensorFusion #ComputerVision #DeepLearning #MLOps #ModelInference #EmbeddedAI #Signalprocessing #PyTorch #TensorFlow #ONNX #Cpp #CUDA #Docker #Kubernetes</li></ul></div><div>
Bei Interesse bewirb dich bitte ausschlie&szlig;lich direkt &uuml;ber unsere Homepage mit deinem aktuellen Lebenslauf sowie den Links zu deinem LinkedIn- und GitHub-Profil.</div><div>
Bei Fragen kannst du dich jederzeit gerne per E-Mail (nathalie@the-formula.de) oder per WhatsApp (+4915733914408) bei uns melden.</div><div>
Wir feiern Vielfalt.
Deshalb begr&uuml;&szlig;en wir ausdr&uuml;cklich alle Bewerbungen &ndash; unabh&auml;ngig von Geschlecht, geschlechtlicher Identit&auml;t oder Ausdruck, sexueller Orientierung, Alter, ethnischer oder sozialer Herkunft, Religion oder Weltanschauung, k&ouml;rperlichen F&auml;higkeiten, Familienstand, &auml;u&szlig;erem Erscheinungsbild oder jeder anderen Eigenschaft, die nach geltendem Recht kein Auswahlkriterium sein darf. Wir sind fest davon &uuml;berzeugt, dass vielf&auml;ltige Perspektiven, Erfahrungen und Lebenswege Teams bereichern und zu besseren Entscheidungen f&uuml;hren.</div></div>

Senior Machine Learning Engineer (d/m/w) Edge ML und IoT, Deutschland remote

develop

<div>
 
 
 AI/ML Engineer | B2 German + English | AI Transformation | Global Scale-Up
 
 
 
 
 
 
 I am working with an incredibly well-funded, establishing global company that is reinventing the future of work by acquiring services businesses and transforming them from the inside out using frontier AI.
 
 
 
 
 
 My client are expanding their team globally and looking for a Senior ML/AI Engineer to design, deploy, and scale real-world AI systems that turn complex, legacy workflows into production-grade business value.
 
 
 
 
 
 
 
 Skills:
 
 
 
 <ul>
 <li>
 AI/ML System Design
 </li>
 <li>
 Production-grade Python
 </li>
 <li>
 LLMs &amp; Agentic AI
 </li>
 <li>
 Retrieval-Augmented Generation (RAG)
 </li>
 <li>
 Computer Vision
 </li>
 <li>
 Cloud &amp; ML Ops
 </li>
 <li>
 Reinforcement Learning
 </li>
 <li>
 Data Engineering (Messy/Legacy Data)
 </li>
 <li>
 Commercial and Product Mindset
 </li>
 </ul>
 
 
 
 
 
 
 Information:
 
 
 
 
 4/5 stage interview process
 
 
 Berlin based ideal (Hybrid) &ndash; 2 days on-site ideal,
 
 
 B2 German &amp; English speaking
 
 
 Salary: &euro;100,000 &ndash; &euro;150,000
 
 
 
 
 
 If this sounds interesting and you would like to learn more, please apply and or reach out to me on LinkedIn and we can set up a call!
 
</div>

Senior Machine Learning Engineer

Kaiko Systems GmbH

<div>Kaiko Systems is a Berlin-based maritime technology company making global shipping safer and smarter. Our AI-powered platform helps shipping companies digitalize vessel inspections, compliance, and fleet health, and is trusted by 40+ customers worldwide. In 2026 we joined forces with UniSea, a leading Norwegian maritime software provider, combining startup pace with the strength of an international group.

We are now looking for a Tech Lead to run our Berlin engineering team day-to-day: a hands-on engineer who prototypes the hard problems, allocates the right people to the right work, mentors the team, and turns architectural direction from our CTO and VP Engineering into a plan the team can execute on. You will report directly to the CTO.
<h2 class="jobSectionHeader">
Tasks</h2>
<ul><li>Prototype the hard problems yourself. When product direction is unclear, you write the spike: small, ugly, fast, built to surface the real complexity. You hand the load-bearing core to the team, stay in the loop while they scale it, and defend the architectural choices that came out of the prototype.</li>
<li>Run the team day-to-day: standups, 1:1s, performance conversations, hiring loops, the engineering side of the on-call rotation. You set the cadence and the cadence holds.</li>
<li>Allocate engineers to projects based on real knowledge of their strengths, weaknesses, and where they need to grow. You make those calls and you defend them.</li>
<li>Mentor and grow people. Give hard feedback the day it is relevant, not at review season. Spot the engineer who is stuck and unstuck them.</li>
<li>Extract architectural guidance from the CTO and VP Engineering and turn it into a plan the team can execute on. Architectural decisions sit with them; landing those decisions sits with you.</li>
<li>Stay hands-on: write production code, review the hard MRs, defend simplicity over premature abstraction, push back on shipping blockers.</li>
<li>Continuously improve how we work &mdash; engineering process, tools, standards &mdash; as we grow within the UniSea Group.</li>
</ul><h2 class="jobSectionHeader">Requirements</h2>
<ul><li>2&ndash;5+ years leading or managing a team of engineers; you have hired, mentored, given hard feedback, and made calls that did not work and learned from them. Depth matters more than years.</li>
<li>Engineer first in your identity. You enjoy the code, you read other people's code, and you have strong, defendable opinions on language and framework choice, testing posture, and abstraction level.</li>
<li>Genuinely hands-on. Strong on at least one of: Python / Django, TypeScript / React, infra (Docker / Postgres / cloud). Comfortable reading the others. You can still write production code today.</li>
<li>Earned soft skills. You can disagree with senior people and have them think more of you afterward. You can give an engineer feedback that lands. You can read a room.</li>
<li>Real track record of growing people. You can name engineers who grew under you, what they grew into, and what you did to help.</li>
<li>Resource-allocation instinct based on real knowledge of people, not a spreadsheet.</li>
<li>Rapid-prototyping reflex. When you do not know how hard a piece of work is, your instinct is to write code, not to schedule a meeting.</li>
<li>Production-grade taste. You know the difference between a spike and a shippable system, and you build prototypes that can grow into the real thing without a full rewrite.</li>
<li>Fluent English. German is not required.</li>
<li>Based in Berlin or willing to relocate. Flexible on office attendance, but close enough that &quot;hey, let's meet tomorrow&quot; actually works.</li>
</ul>
Nice to have
<ul>
<li>Maritime, logistics, or other physical-world-meets-software domains.</li>
<li>Computer-vision or LLM-agent product experience.</li>
<li>Experience at profitable or capital-efficient companies; we are not a &quot;raise and burn&quot; shop.</li>
</ul><h2 class="jobSectionHeader">Benefits</h2>
<ul><li>Real ownership of a ~10-engineer team shipping to global shipping operators.</li>
<li>A codebase that does serious work: AI on the customer path, offline PWA syncing event-sourced state from on-vessel installations, computer-vision pipelines on production traffic.</li>
<li>The stability of an international group (UniSea) combined with the speed and ownership of a startup.</li>
<li>Direct exposure to the CTO and CEO; in the room for the calls that matter.</li>
<li>A diverse, international team of maritime experts, engineers, and commercial talent.</li>
<li>Central Berlin office at M&uuml;nzstra&szlig;e (Mitte).</li>
<li>Competitive salary, meaningful equity, modern equipment.</li>
<li>Regular team events, offsites, and a culture that takes itself seriously without being stiff.</li>
</ul>
We would love to hear from you. Send us your CV plus a short paragraph telling us: (a) the hardest team-management call you have made, (b) a project where you prototyped something and handed it off, and (c) an engineer who grew under you and what they are doing now.

Our process is fast and respectful of your time: an intro call with the VP Engineering or CTO, a deep technical conversation with the CTO, two team conversations with senior engineers, and a final chat with the CEO. You will hear back from us within a few days at every stage.</div>

Tech Lead (m/f/d)

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