Haldorix

Introduction to the position

Join Haldorix, a startup studio turning real-world operational challenges into scalable business opportunities through technology. We identify recurring problems in industries such as manufacturing, retail, and logistics, and transform them into ventures with measurable impact.We’re looking for a Tech Architect to lead the design and validation of a real-time industrial vision system for monitoring productivity on textile production lines. This is an intensive initiative aimed at delivering a fully functional, field-ready solution, ideal for an engineer who thrives on fast execution and tangible results.

Your role

- Architect & Design: Define the overall system architecture and ensure cohesion across components and technologies.- Field Deployment: Oversee on-site installation and calibration of AprilTags, cameras, and network components.- Quality Assurance: Coordinate QA activities and conduct end-to-end acceptance testing in production environments.- Monitoring Setup: Configure and validate observability dashboards using Grafana and business-specific KPIs.- Documentation: Produce comprehensive technical and operational documentation to support deployment and scalability.- Cross-Functional Collaboration: Act as the bridge between technical and business stakeholders, ensuring alignment between field needs and system capabilities.- Continuous Improvement: Identify optimization opportunities and propose architecture adjustments based on real-world performance feedback.

Your team

You’ll join a multidisciplinary task force of engineers, computer-vision experts, and product innovators working under Haldorix’s venture-building model. Collaboration is tight-knit and execution-driven. Every decision directly impacts the success of the project. You’ll work alongside technical leads, and collaborate with on-site operators to validate system performance in real conditions.

Your qualifications

Required- 3+ years of experience in system architecture- Strong understanding of resilient, distributed systems design- Hands-on knowledge of Kubernetes, Prometheus, and Grafana- Familiarity with Computer Vision systems and on-field hardware calibration- Solid foundation in QA methodologies and field validation processes- Excellent communication and documentation skills in English and/or FrenchNice to Have- Prior experience in industrial automation or IoT environments- Familiarity with AprilTags, camera calibration, or real-time data pipelines- Exposure to Python, FastAPI, or edge-AI deployment workflows- Previous work in a startup environment

Benefits

- Immediate impact through a high-intensity, real-world project- Opportunity to shape a new industrial AI venture from its early stages- Work directly with cross-disciplinary experts at the frontier of AI and operations- A mission-driven environment that values autonomy, clarity, and purpose

Recruitment process

Jobzyn AI interview (25–45 min)

Technical interview (1h) with the Lead Developer or Technical Architect

Practical test (2–3h) based on a real-world use-case

Final interview with the team and partners

Introduction to the position

Join Haldorix, a startup studio turning real-world operational challenges into scalable business opportunities through technology. We identify recurring problems in industries such as manufacturing, retail, and logistics, and transform them into ventures with measurable impact.We’re looking for a Lead Computer Vision Engineer to own the video-processing and calibration pipeline of a real-time industrial vision system for textile production monitoring. This is an intensive mission to deliver a fully functional and production-ready system, ideal for a seasoned engineer who thrives under pressure and in fast-moving environments.

Your role

- Lead Computer Vision Pipeline: Oversee the full video-processing chain from acquisition to detection, tracking, and visualization.- Geometric Calibration: Compute homographies to transform pixel coordinates into millimeter-scale real-world metrics.- Model Optimization: Manage and fine-tune FACT-tiny for high performance and robustness in real-time inference.- System Reliability: Ensure consistent mAP metrics, monitor model drift, and troubleshoot in live environments.- Documentation: Maintain structured FSM (Finite State Machine) diagrams and model specifications.- Cross-Functional Collaboration: Work closely with the lead developer and product architect to align system components.- Performance Tuning: Optimize GPU usage, latency, and throughput for on-edge or on-premise deployments.- Knowledge Transfer: Support internal teams through clear documentation and hands-on mentorship.

Your team

You’ll work within a small high-impact team composed of talented engineer. Collaboration is fast, pragmatic, and outcome-driven. You’ll collaborate with the Lead Developer and Lead architect to ensure that technical design aligns with measurable field impact.The environment is dynamic, collaborative, and experimentation-friendly, exactly where applied research meets operational excellence.

Your qualifications

Required- 3+ years of hands-on experience in Computer Vision (OpenCV, detection, tracking).- Understanding of camera calibration and 2D/3D projective geometry.- Proficiency in Python with scientific and vision libraries (NumPy, OpenCV, cv2).- Strong understanding of Deep Learning architectures for video processing.- Experience optimizing GPUs for real-time performance.Nice to Have- Prior work in industrial automation, or IoT vision systems.- Familiarity with edge deployment and lightweight inference frameworks.- Knowledge of DevOps workflows (Docker, Kubernetes, CI/CD).- Experience mentoring or collaborating with multi-disciplinary teams.- Strong documentation and communication skills in English or French.

Benefits

- Direct, measurable impact on industrial productivity.- Exposure to real-world AI challenges with immediate operational deployment.- Opportunity to shape and deliver a full system end-to-end.- Work alongside a team of experts combining AI, software, and industry know-how.

Recruitment process

Jobzyn AI interview (25–45 min)

Technical interview (1h) with the Lead Developer or Technical Architect

Practical test (2–3h) based on a real-world use-case

Final interview with the team and partners

Introduction to the position

Join Haldorix, a startup studio turning real-world operational challenges into scalable business opportunities through technology. We identify recurring problems in industries such as manufacturing, retail, and logistics, and transform them into ventures with measurable impact.We’re looking for a Full-Stack Python/Video Processing engineer capable of owning the full data and event pipeline from video capture to real-time business logic execution.

Your role

- Design & Implementation: Build the end-to-end pipeline for real-time video capture, analysis, and KPI generation.- Video Processing: Implement multi-stream 2K video ingestion and compression pipelines using FFmpeg and RTSP.- System Architecture: Develop robust state machines (FSM) to orchestrate production cycles and handle asynchronous events.- Realtime Workers: Create real-time workers for station- and line-level KPIs, ensuring accuracy and low latency.- Automation: Generate regions of interest (ROI) automatically using AprilTags to streamline calibration and setup.- Benchmarking: Conduct latency and performance tests to guarantee reliability under production constraints.- Integration: Collaborate with peer engineers to ensure seamless data-flow via MQTT and REST APIs.

Your team

You’ll join a compact, high-velocity engineering squad within Haldorix’s industrial AI venture. The team combines expertise in computer vision, real-time systems, and full-stack development. You’ll work closely with the venture’s lead engineer and lead architect.

Your qualifications

Required- 2+ years of experience in Python development (including async/threading patterns).- Proven experience in video processing, streaming, or FFmpeg pipelines.- Strong knowledge of real-time systems and event-driven architectures.- Hands-on experience with MQTT, REST APIs, and state machine design.Nice to Have- Experience in computer vision or industrial AI systems.- Familiarity with AprilTags or similar object-tracking technologies.- Understanding of edge computing or on-premise deployment.- Exposure to distributed systems and performance benchmarking.

Benefits

- Work on a cutting-edge industrial AI system with immediate real-world impact.- Join a venture studio that values experimentation and technical mastery.- Collaborate with experts across AI, vision, and hardware integration.- Experience the fast-paced, startup-style delivery of a complete system in record time.

Recruitment process

Jobzyn AI interview (25–45 min)

Technical interview (1h) with the Lead Developer or Technical Architect

Practical test (2–3h) based on a real-world use-case

Final interview with the team and partners

Introduction to the position

Join Haldorix, a startup studio turning real-world operational challenges into scalable business opportunities through technology. We identify recurring problems in industries such as manufacturing, retail, and logistics, and transform them into ventures with measurable impact.We’re looking for a Computer vision/Machine Learning Engineer – Inference & Model Deployment to join our industrial vision venture. You’ll play a key role in developing a real-time computer vision system for monitoring productivity in textile production lines.

Your role

- Optimization & Deployment: Export and optimize deep learning models using ONNX and TensorRT (INT8, FP16) for efficient inference on GPU.- Active Learning Loop: Manage data collection, annotation, and correction pipelines within CVAT to continuously improve model performance.- Performance Benchmarking: Conduct GPU stress tests and benchmark latency, throughput, and accuracy across deployment environments.- Validation & QA: Lead field validation sessions, perform detailed QA checks, and ensure robustness in real-time production conditions.- Automation & Scalability: Develop scripts and tools to streamline model conversion, quantization, and deployment workflows.- Collaboration & Documentation: Work closely with CV and backend engineers to integrate optimized inference pipelines and document performance metrics.- Continuous Improvement: Analyze bottlenecks, propose optimizations, and refine the active learning feedback loop for model accuracy.- Testing Culture: Contribute to building a strong testing and profiling culture around ML models in production.

Your team

You’ll be part of a small, agile engineering team dedicated to building intelligent vision systems for industrial environments. Working alongside computer vision specialists, data engineers, and QA professionals, you’ll report directly to the Technical Lead overseeing system integration and infrastructure. Collaboration, iteration, and precision define our team culture. Every member is both an engineer and a problem solver focused on creating tangible field impact.

Your qualifications

Required:- 2+ years of hands-on experience in ML model deployment and inference optimization- Strong expertise with TensorRT, ONNX, and GPU performance optimization- Experience with quantization techniques (INT8, FP16)- Proficiency in Python for scientific computing and QA/testing workflows- Familiarity with video annotation tools like CVAT or Label Studio- Proven ability to conduct GPU benchmarking and profiling- Strong attention to detail and commitment to production-grade qualityNice to Have:- Experience in industrial computer vision or real-time systems- Familiarity with Active Learning workflows and auto-annotation techniques- Knowledge of Docker or Kubernetes for ML model deployment- Understanding of CI/CD for ML pipelines- Previous experience in manufacturing, logistics, or IoT environments

Benefits

- Join a startup studio building high-impact industrial ventures from the ground up- Work on cutting-edge real-time computer vision systems deployed in production- Collaborate with a skilled, multidisciplinary team driven by innovation- Gain deep expertise in model optimization and production ML

Recruitment process

Jobzyn AI interview (25–45 min)

Technical interview (1h) with the Lead Developer or Technical Architect

Practical test (2–3h) based on a real-world use-case

Final interview with the team and partners

Introduction to the position

Join Haldorix, a startup studio turning real-world operational challenges into scalable business opportunities through technology. We identify recurring problems in industries such as manufacturing, retail, and logistics, and transform them into ventures with measurable impact.We’re looking for a Computer Vision / Machine Learning Engineer - Model training to join our team. You’ll develop a real-time productivity monitoring system for textile production lines from model fine-tuning to deployment.

Your role

As a Machine Learning Engineer – Video Model Training, you will be responsible for designing, fine-tuning, and deploying video-based models for industrial vision. Your key responsibilities include:- Research & Discovery - Analyze existing datasets and identify optimal data sampling and labeling strategies. - Evaluate prior model performance and determine improvement paths through Active Learning.- Design & Definition - Set up and structure video training pipelines for short clips. - Design and test data augmentation workflows for robustness.- Execution & Collaboration - Fine-tune the FACT-tiny architecture on domain-specific data. - Implement and monitor GPU-optimized training using mixed precision and TensorBoard. - Manage model checkpoints and retraining cycles during Active Learning.- Feedback & Iteration - Conduct iterative experiments to maximize accuracy and inference efficiency. - Work closely with the engineering team to integrate the model into the production system.- Innovation & Learning - Explore alternative architectures such as SlowFast or 3D CNNs for performance comparison. - Document key findings and best practices for future model deployments.

Your team

You’ll join a small, high-performing engineering team working at the intersection of computer vision, data, and industrial operations. The team combines expertise from AI research, software engineering, and product integration, and operates in short, focused sprints.You’ll report directly to the **Lead computer vision engineer**, collaborating daily with backend and computer vision engineers to deliver an end-to-end operational solution.

Your qualifications

Required- 2+ years of experience in Deep Learning model training and optimization.- Strong proficiency with PyTorch.- Experience with video architectures such as FACT, SlowFast, or 3D CNNs.- Solid understanding of data augmentation tools (Albumentations, imgaug).- Familiarity with GPU optimization, mixed precision, and training monitoring (TensorBoard).- Proven ability to iterate quickly and improve model performance under time constraints.Nice to Have- Experience in industrial vision or manufacturing contexts.- Exposure to MLOps workflows (versioning, checkpoints, pipeline reproducibility).- Familiarity with Active Learning loops in computer vision.- Hands-on experience with real-time inference pipelines or edge deployments.

Benefits

- Opportunity to work on a cutting-edge applied AI project with real industrial impact.- Close collaboration with an expert technical team and startup founders.- Freedom to experiment, learn, and push the boundaries of real-time vision systems.

Recruitment process

Jobzyn AI interview (25–45 min)

Technical interview (1h) with the Lead Developer or Technical Architect

Practical test (2–3h) based on a real-world use-case

Final interview with the team and partners

Introduction au poste

En tant que Head of Sales, vous jouerez un rôle clé dans la construction et la mise en place de la stratégie commerciale. Votre expertise en vente SaaS (obligatoire) sera essentielle pour transformer la traction initiale en croissance scalable.

Votre rôle

•Définir, piloter et exécuter la stratégie commerciale globale pour l’ensemble des ventures Haldorix.•Structurer un modèle de vente B2B SaaS scalable : segmentation, ICP, pricing, funnels commerciaux.•Construire le pipeline, développer les opportunités stratégiques et conclure les deals clés avec les grands comptes.•Mettre en place les processus, outils et KPIs commerciaux pour assurer une visibilité et une performance optimale.•Collaborer étroitement avec les équipes Produit, Venture Building et Marketing pour aligner offre, messages et besoins terrain.•Recruter, manager et faire monter en compétence une équipe commerciale internationale à mesure de la croissance du portefeuille.•Assurer une veille concurrentielle et marché pour affiner les stratégies de positionnement.•Représenter Haldorix et ses ventures lors d’événements, salons, rencontres clients et partenaires industriels.

Votre équipe

Vous rejoignez une structure entrepreneuriale, pluridisciplinaire et orientée impact :•Venture Builders : experts marché consolidant les besoins, validant les opportunités et lançant les MVP.•CTO & équipes tech : développement des produits SaaS et industrialisation technologique.•Founders & Partners : pilotage stratégique, financement, vision long terme.Collaboration étroite, cycles rapides d’itération et culture orientée solutions.

Vos qualifications

Obligatoires :•Expertise démontrée en vente SaaS B2B (obligatoire).•Expérience en création ou structuration d’une fonction Sales.•Solide maîtrise des cycles de vente complexes (mid-market & enterprise).•Compétences avancées en négociation, closing et gestion de comptes stratégiques.•Expérience dans la construction d’un pipeline fiable et dans l’utilisation d’outils CRM.•Forte capacité analytique (KPIs, forecasting, conversion funnels).•Leadership, culture du résultat et capacité à emmener une équipe.•Anglais et français professionnels.Nice to have : •Expérience au sein d’une start-up early stage ou environnement entrepreneurial.•Connaissance des secteurs industriel, retail ou logistique.•Expérience en internationalisation ou déploiement de nouvelles offres.•Réseau actif dans les écosystèmes Tech / SaaS / Industrie.

Processus de recrutement

Pré-sélection CV : analyse du parcours, des réalisations commerciales et de l’adéquation avec la mission.

Entretien IA : échange structuré pour évaluer compétences, motivations et aptitudes comportementales.

Rencontre des équipes Haldorix : discussions avec les Venture Builders et CTO pour valider le fit stratégique et opérationnel.