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Principal MLOps Engineer
PresencialTiempo completoAI EngineeringCybersecurity
Design and scale ML and LLMOps platforms that enable data scientists and security researchers to train, deploy, serve, and continuously improve advanced AI systems.
Responsabilidades
- Design and optimize distributed GPU infrastructure for LLM and SLM training and fine-tuning
- Architect automated continuous training and deployment pipelines across the ML lifecycle
- Own production model-serving architecture, balancing latency, throughput, and GPU utilization
- Build observability systems for model performance, data drift, and compute metrics
- Feed monitoring insights into automated training and continuous-improvement workflows
- Partner with data scientists and security researchers to productionize complex model architectures
- Integrate ML platforms with core cloud infrastructure in collaboration with DevOps teams
Requisitos
- 4+ years of hands-on experience as a Senior ML Engineer, MLOps Engineer, or Backend Platform Engineer in cloud environments
- Experience managing the technical lifecycle of classic ML, LLM/SLM, and agentic or RAG systems
- Expert Python skills for ML infrastructure, pipelines, and automation
- Experience designing scalable data preparation and processing pipelines
- Experience with distributed multi-GPU training using tools such as PyTorch, DeepSpeed, Megatron-LM, or cloud-native training infrastructure
- Strong knowledge of deep learning concepts, training dynamics, and optimization techniques
- Infrastructure expertise with AWS, Azure, or GCP managed AI platforms and services
- Experience integrating CI/CD patterns such as GitLab CI or GitHub Actions into software and model delivery
- Proficiency with AI development tools and ecosystems for generating, reviewing, and testing code
- Applicants must be able to work in Israel; immigration sponsorship is not available
Se valora
- Strong experience with the GCP ecosystem
- Background in data science or deep learning workflows
- Cybersecurity domain knowledge