Machine Learning Engineer at MLP

Department: Information Technology

Setup: On-site
Type: Full-time
Level: senior
Posted: Jun 4, 2026

Description

The Machine Learning Engineer will lead AI/ML infrastructure development for autonomous agents, machine learning systems, and enterprise AI applications. Responsibilities include transforming prototypes into production systems, designing federated AI ecosystems, orchestrating distributed agent deployment, building evaluation and observability pipelines, integrating AI tools into CI/CD, and teaching infrastructure best practices across teams. The role requires a relevant bachelor’s, master’s, or PhD degree with the specified years of experience, Python and PyTorch proficiency, distributed systems knowledge, and production containerization experience. The Israel office is in the Bursa area of Ramat Gan and the role is on-site.

Required Skills

Python
PyTorch
Agent orchestration
Docker
Kubernetes
MLOps
LLM routing
Vector databases
RAG

Additional Information

Minimum Education: Bachelor’s degree in Computer Science, Data Science, Machine Learning, or a related field with 6+ years of experience; alternatively, a master’s degree with 4+ years of experience or a PhD with 2+ years of experience.
Required Previous Experiences: Experience with AI/ML infrastructure, agent orchestration, or similar AI-powered development tools.
Experience with Docker, Kubernetes, and container orchestration in production environments.
Preferred Qualifications: Experience with AWS, Azure, or GCP and infrastructure-as-code tools.
Experience with MLOps and production machine learning workflows.
Experience building agentic AI systems with LangGraph, LangChain, PydanticAI, LLM integration, tool calling, structured outputs, and MCP.
Solid foundation in classical machine learning, including supervised and unsupervised learning, feature engineering, classification, regression, clustering, and model evaluation.
Strong knowledge of vector databases, embedding pipelines, and retrieval-augmented generation architectures.