Senior ML Algorithm Engineer

Description

Chips Talk, We Listen

proteanTecs is a game-changing startup that's giving advanced electronics the power to report on their own health. In a digital world built for autonomous driving, cloud computing, and AI, we depend on computing systems daily. But how can we guarantee their safety, reliability and functionality? proteanTecs is the first-ever company to provide visibility into next-gen chips while they are operating, based on the power of on-chip monitoring, machine learning, and data analytics.

Here at proteanTecs, you'll be part of a team that's unlocking deep insights to make electronics more reliable, efficient, and high-quality. We're trusted by industry leaders in data centers, automotive, communications, and consumer devices - we work with the world's largest and most notable companies in tech.

Why proteanTecs is a great place to work:

• Fast-paced and impactful: We're a mission-driven startup, so you'll tackle new challenges daily, wear many hats, and see your work directly influence the future of electronics.
• Supportive company culture: Learn from the best. Our 200+ team members are experts in their field with a proven track record of success, and they're committed to fostering a collaborative and supportive work environment.
• International presence: We're a multinational company with a diverse team across multiple locations around the globe. You'll collaborate on projects with international impact, gaining a global perspective of the tech industry.
• Work with industry leaders: Our solutions are used by the biggest names in tech. You'll be part of the team creating the next generation of groundbreaking products.
• Cutting-edge playground: We use the latest machine learning, platforms, and tools to push boundaries and achieve breakthroughs.
• Real-world impact: Our work keeps data centers, cars, and other critical systems running smoothly. Your work will directly contribute to safer, more reliable electronics.
• We are here for the win: Backed by industry veterans and leading investors, we offer a stable and secure work environment with plenty of room for growth.

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: 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)

Advantage

• 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

Responsibilities

• 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 workflows.