Senior ML Algorithm Engineer

proteanTecs is a dynamic, fast-paced start-up revolutionizing the reliability of electronics. In a world where machines are increasingly responsible for critical functions in our lives, sudden failure is not an option.

We’ve developed a cutting-edge, cloud-based platform that leverages data created by chip-embedded Agents (IPs) combined with advanced machine learning to detect anomalies and predict failures before they occur.

Our solutions deliver unprecedented insights across the electronics value chain—from Chip Vendors to System Vendors and Digital Service Providers. Founded in 2017 by seasoned veterans of Mellanox Technologies, proteanTecs is backed by leading global investors and powered by deep industry expertise.

We bring together a highly interdisciplinary team—from SaaS and Machine Learning experts to top designers in Chips, Circuits, and EDA. Collaboration is central to our culture—we learn from each other and push boundaries together.

We are looking for a Senior Machine Learning Algorithm Engineer who is passionate about solving complex, real-world problems at the intersection of hardware and software.

Location: Haifa \ Tel-Aviv in hybrid model.

Requirements:

• B.Sc. in Electrical Engineering – MUST
• 5+ years experience in algorithm development, preferably in complex, data-intensive environments
• Deep expertise in Python, including statistical and machine learning packages
• Proven experience across all algorithm development phases: research, implementation, testing, deployment, and debugging· Familiarity with testing frameworks (e.g., unit tests, E2E tests, performance and memory profiling)
• Intensive usage of AI coding tools like Cursor or equivalent (e.g., GitHub Copilot, CodeWhisperer)
  
  

• M.Sc. or higher in Electrical Engineering, Computer Science, or a related field
• Prior experience with:
• HW/SW integration or ATE/Chip testing
• Version control systems (e.g., Git) and CI/CD tools
• Distributed compute frameworks (e.g., Spark, MLRun)
• Containerization and cloud orchestration (e.g., Kubernetes, cloud APIs)
• Business intelligence tools (e.g., Tableau or equivalent)
• AI platforms and agents that interface with model training, data annotation, performance monitoring, or autonomous debugging
• Familiarity with chip production or design methodologies
  
  

• Develop advanced ML algorithms using data from proteanTecs Agents embedded in silicon. Example domains include:
• Lifetime predictions
• Clustering and dimensionality reduction
• Parametric modeling and screening
• Time-series forecasting
• Lead end-to-end algorithm lifecycle: ideation → research → POC → design → implementation → validation → deployment.
• Collaborate closely with cross-functional teams and directly with customers to continuously refine and enhance deployed solutions.
• Drive integration of AI-enhanced tools and intelligent pipelines into ML workflow.