Machine Learning Software Engineer - Optical Engineering

Molex possesses a rich heritage in the optical industry. We provide the highest performing and field-proven wavelength management solutions, from components and modules to integrated line-cards. Continuous innovation in passive component function integration, miniaturization, and manufacturing automation, cutting edge WSS and amplification technology and comprehensive optical, mechanical, electrical and software design capabilities enable us to serve the needs of high-density, high-bandwidth, and flexible optical networks of telecom, datacom, hyperscale datacenter and supercomputing.

We are seeking a Machine Learning Software Development Engineer with industry experience to join our Optical Line Systems (OLS) Product Development team. In this role, the Software Development Engineer will design and deliver large-scale system simulation and AI-driven intelligence for next-generation optical networks, spanning offline system software validation and online autonomous operations.

The Software Development Engineer will develop mature machine learning and system modeling techniques to solve complex, real-world problems in high-reliability, distributed data center interconnect (DCI) systems operating at global scale. This role offers high ownership, including responsibility for building and advancing the Intelligence Layer of our Long-Haul Optical Line Systems (OLS).

This role can be based in Fremont, Ottawa, or remotely in the United States.

• Design, develop, and maintain scalable simulation frameworks to model the behavior of large, complex systems, enabling validation of software interfaces, controlling logic, performance, scalability, and fault scenarios.
• Leverage simulation and real-world operational data to enable hardware-independent testing, accelerate software development, and improve automated validation and continuous integration workflows.
• Develop and deploy machine-learning-based solutions to improve system reliability, including anomaly detection, root-cause analysis, predictive maintenance, and automated recovery mechanisms.
• Apply a range of matured machine learning techniques to analyze telemetry, logs, and performance data from production systems.
• Collaborate with cross-functional engineering teams to integrate simulation and ML capabilities into end-to-end testing, monitoring, and operational workflows.

• Master's or PhD in Machine Learning, Computer Science, Software Engineering, Electrical Engineering, or a related field, with a strong focus on machine learning and/or system simulation.
• At least 3 years of hands‑on industry experience in software development, system simulation, or AI‑driven analytics.
• Expertise in machine learning application, particularly model evaluation, validation, and deployment considerations.
• Advanced expertise in Python and its ML ecosystem (e.g., PyTorch, Tensor Flow, scikit‑learn, Pandas).
• Experience with C++, especially for simulation.
• Experience hands‑on with the creation of a digital twin.
• Experience with testability, code quality, and version control.
• Experience with ML models for production/manufacturing environments.

• Experience in networking, telecom, optical systems, or distributed infrastructure.
• Familiarity with one or more of the following:
• Long‑haul optical systems (e.g., amplifiers, ROADM/WSS, OCM, Raman, OSC).
• System software validation, CI/CD pipelines, or automated testing frameworks.
• Prior experience deploying machine learning models into production or operational environments.

For this role, we anticipate paying $150,000 - $250,000 per year. This role is eligible for variable pay, issued as a monetary bonus or in another form.

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