10 дней назад
Senior MLOps Engineer (AI)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior MLOps Engineer (AI): Building and operating infrastructure for training, fine-tuning, evaluating, deploying, and monitoring NLP and LLM models with an accent on scalable GPU/CPU environments, CI/CD, and real-time inference. Focus on optimizing distributed training, model serving performance, cost efficiency, observability, and production reliability.
Location: Tel Aviv, Israel; onsite office role
Company
is building an AI Security and Governance Platform that provides visibility and protection across the AI lifecycle.
What you will do
- Design, build, and maintain pipelines for training, fine-tuning, evaluating, and deploying NLP and LLM models across GPU and CPU environments.
- Implement CI/CD workflows for ML models, including benchmarking, testing, performance gates, and production deployment.
- Select and optimize serving frameworks for low-latency, high-throughput inference.
- Manage training environments, experiment tracking, model registries, artifact versioning, and distributed training systems.
- Monitor and optimize production models for performance, cost efficiency, availability, and observability.
- Partner with DevOps, Backend, Data, and Product teams to establish ML infrastructure.
Requirements
- 5+ years of experience in software engineering, MLOps, or ML engineering, including deploying ML models to production.
- Strong Python skills and understanding of transformer architectures, tokenization, PyTorch, and HuggingFace.
- Experience deploying and scaling LLMs for real-time inference on SageMaker, Vertex AI, or similar platforms.
- Expertise in GPU optimization, distributed training, and CPU-based inference optimization.
- Strong cloud and Kubernetes experience with EKS, GKE, AKS, Helm, Terraform, and CI/CD for ML.
Nice to have
- Experience building or operating internal ML platforms.
- Knowledge of LLM evaluation frameworks for quality, robustness, or observability.
- Experience with data-driven ML operations, cost optimization, and model observability.
- Understanding of security implications in ML pipelines.
- Familiarity with multi-model orchestration, vector databases, or retrieval pipelines.
Culture & Benefits
- Bright, spacious, dog-friendly office near public transportation, the Hashalom train station, and the Light Rail.
- Team bonding activities, company retreats, happy hours, and holiday gifts.
- Pilates classes, monthly lunch budget, dinners, and a stocked kitchen.
- Supportive, people-first culture with teams across Tel Aviv, the US, the Netherlands, and London.
- Pension, Keren Hishtalmut, and options to share in company growth.
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