Forward Deployed AI/ML Model Engineer
Hybrid · Zürich, Zurich, Switzerland
Job Summary
Forward Deployed AI/ML Model Engineer responsible for deploying, tuning, and owning AI/ML models with customers; designing and delivering AI/ML products in collaboration with UX, product management, and engineering; building scalable model training/inference pipelines, including data assets and validation; leveraging ML lifecycle tools (MLFlow, Nvidia NeMo, Ray, Torch Distributor) and integrating with Spark-based data pipelines; driving architectural evolution for scalable, secure, and reliable systems at ISO 27001 level; supporting deployment/monitoring/optimization in varied production environments (including air-gapped scenarios with/without GPUs); contributing to model and data pipeline design decisions for Kubernetes deployment; operating in a hybrid work environment in Zurich, Switzerland with international exposure and opportunity for growth.
Required Qualifications
- University degree in Computer Science, Engineering, or equivalent
- 5+ years of hands-on AI/ML model engineering experience
- Experience with LLM fine-tuning, GNN design and data engineering technologies
- Experience with security-sensitive product deployment scenarios is an advantage
- Strong understanding of distributed systems and ML platforms (LangChain, NeMo, PyTorch, SparkML)
- Experience with MLops (MLFlow, Kubernetes)
- Proficiency in clean architecture and modern software engineering practices
- Familiarity with ML stack (Spark, MLFlow, Delta Lake, PyTorch Distributed, TensorFlow, ONNX) and backend technologies such as Helm and Kubernetes
- Ability to collaborate across cross-functional and customer/internal teams
- Excellent problem-solving, debugging, and troubleshooting skills
- Strong verbal and written English communication skills
Desired Qualifications
- 5+ years AI/ML model engineering experience
- Experience with LLM fine-tuning, GNN design and data engineering technologies
- Strong understanding of distributed system design and ML platforms (LangChain, NeMo, PyTorch, Spark)
- Experience with MLops (MLFlow, Kubernetes)
- Experience with cloud-native development and Helm
- Experience collaborating across cross-functional teams
- Excellent problem-solving and communication skills in English
Apply with one swipe on Sorce. We auto-fill applications and apply on your behalf — no cover letters, no 40-minute forms.
Hiring someone like this?
Get your role in front of qualified candidates on Sorce.