Dein persönlicher KI-Karriere-Agent
ML/Data Infrastructure Engineer (m/w/x)
Building and operating data/ML infrastructure for drone inspection software. Python and AWS S3/compute experience required. Flexible schedules, 25 vacation days.
Deine Match-Analyse
Warum dieser Job zu dir passt
Mögliche Lücken
Tipps für deine Bewerbung
Anforderungen
- 3+ years data engineering, MLOps, ML infrastructure, or related software engineering
- Strong Python and software engineering skills
- Hands-on data storage, databases, and data processing experience
- Practical AWS experience, particularly S3 and cloud compute/storage
- ML lifecycle experience (dataset/model versioning, experiment tracking, training orchestration, model registries, ML CI/CD)
- ML dataset experience (curation, versioning, annotation, data quality)
- Experience with Docker, CI/CD, workflow orchestration, or infrastructure-as-code
- Strong understanding of ML engineer practical needs
- Strong ownership and problem-solving skills
- Proficiency in English
- Experience with MLflow, DVC, SageMaker, or similar MLOps technologies
- Experience with annotation platforms and external labeling teams
- Experience deploying ML models to embedded or resource-constrained platforms
- Experience orchestrating pipelines for fine-tuning, evaluation, and low-latency serving of Language Models
Aufgaben
- Build and operate data and ML infrastructure
- Own data collection, preparation, and labeling workflows
- Own training, evaluation, and model deployment workflows
- Transform datasets into structured, versioned, and accessible ML assets
- Enable faster experimentation and reliable model delivery
- Own infrastructure and workflows for ML data pools and datasets
- Ingest, organize, curate, validate, and version raw data
- Host in-house labeling tools and manage annotation workflows
- Ensure seamless data flows between AI engineers and labeling partners
- Automate and maintain ML training infrastructure and workflows
- Automate and maintain ML evaluation and experiment tracking
- Automate and maintain ML reproducibility
- Build tooling and automation for model deployment
- Monitor training and model performance
- Connect production data and failure cases back into the ML development loop
- Provide tools, documentation, and workflows for AI engineers
- Enable AI engineers to go from data to deployable models
Berufserfahrung
Ausbildung
Sprachen
Tools & Technologien
Benefits
- Flexible schedules
- Remote work up to 2 days/week
- Public holidays
- Comprehensive accident insurance
- Additional days off based on seniority
- Gym membership discounts
- Sports event discounts
- Swibeco discounts and rewards
- Ski weekend
- Summer barbecue
- After-work gatherings
Von Nejo automatisch aufbereitet
Nejo hat diesen Job automatisch von der Website des Unternehmens Flyability erfasst und die Informationen auf Nejo mit Hilfe von KI für dich aufbereitet. Trotz sorgfältiger Analyse können einzelne Informationen unvollständig oder ungenau sein. Bitte prüfe immer alle Angaben in der Originalanzeige! Inhalte und Urheberrechte der Originalanzeige liegen beim ausschreibenden Unternehmen.
Zur Originalanzeige bei FlyabilityÜber das Unternehmen
Flyability pioneers UAV indoor inspection with Elios, a collision-tolerant flying robot for remote entry into complex indoor spaces.
Nejo bewertet ihn, und bringt ihn danach gemeinsam mit dir in Bestform.
Noch nicht perfekt?
- FlyabilityMachine Learning Engineer - Spatial AI (m/w/x)Vollzeitmit HomeofficeBerufserfahrenPaudex
- Nestlé Operational Services Worldwide SALab Data Technology Specialist (m/w/x)Vollzeitmit HomeofficeBerufserfahrenLausanne
- AdaptyvSoftware Engineer, Backend (m/w/x)VollzeitRemoteBerufserfahrenLausanne
- FlyabilityTechnical Customer Support Specialist (m/w/x)Vollzeitmit HomeofficeBerufserfahrenPaudex
- Isomorphic LabsSenior Security Engineer (AI Safety) (m/w/x)Vollzeitmit HomeofficeSeniorLausanne