Director of Machine Learning Engineering

Director of Machine Learning

This position is for our Pittsburgh, PA office - only apply if you are based there or willing to relocate

At TDK SensEI, we are transforming how industrial customers utilize and interact with sensor data. We specialize in developing advanced AI solutions capable of running directly on edge devices. By processing data at the edge, TDK SensEI enhances real-time decision-making, privacy, security, and cost efficiency. Our offerings include automated machine learning tools, AI-powered condition-based monitoring and predictive maintenance systems, and various sensor devices optimized for low latency and power consumption. Collaborating with leading global companies, we empower teams to effortlessly deploy machine learning solutions for industrial applications with minimal manual effort.

We are looking for a Director and machine learning expert who loves working with sensor data, loves developing novel algorithms, is not afraid of challenging, open-ended problems, and wants to help us shape the future of machine learning in industrial settings. You will be leading a highly capable team of machine learning engineers and will have the opportunity to make a meaningful impact on the growth of a burgeoning industry.

Responsibilities

As a Director of Machine Learning, your responsibilities will include:

• Driving the execution of the long-term implementation approach for the company’s ML product line, focused on machine and factory health and AI agentic solutions aligned with business and product goals.
• Researching and implementing new machine learning techniques for use in TDK SensEI products.
• Overseeing selection and deployment of AI/ML models, including deep learning algorithms, LLMs, and classical algorithms.
• Coordinating and owning delivery across the end-to-end ML lifecycle: research, development, deployment, monitoring, and optimization.
• Evaluating emerging AI/ML trends and providing strong leadership and guidance on how emerging solutions may facilitate improvements and opportunities in the product.
• Representing TDK SensEI at industry events, conferences, and client engagements.
• Managing the resourcing and plans needed to execute the ML engineering roadmap aligned with product and business goals.
• Active leadership for a team of ML engineers - setting strategic direction while delivering hands-on technical leadership and support. Owning the multiple work streams the edgeRX Machine Learning Team balances daily, while also contributing directly to development and research efforts.
• Identifying the key steps required to complete each project, estimate timelines for each phase, and strategically prioritize tasks across the team to ensure efficient execution.
• Building, mentoring, and managing a high-performing teams of ML engineers and data scientists.

Ideal Candidate

• Expertise in one or more specific areas of research: automated machine learning, anomaly detection, condition monitoring, predictive maintenance, neural nets, deep learning, signal processing, and digital imaging
• Computer Science/EE/ECE background (MS or PhD preferred) with strong coding ability and proficiency with Python or other OOP language.
• Proven success in delivering ML/AI solutions (e.g., research publications, open-source contributions, production deployments).
• Demonstrated experience in managing and mentorship of high-performing ML engineers, including staff hiring and career management.

Skills & Requirements

• Machine Learning (expert; at least 5 years industry experience and/or Master’s degree in relevant field)
• Python or other modern OOP language (proficient)
• Data Structures and Algorithms (proficient)
• Deep Learning (proficient)
• Data Structures and Algorithms (familiar)
• Signal Processing (familiar)
• Some travel may be required, including international
• US Work Authorization required

Bonus Qualifications

• Significant work experience deploying production machine learning models for production or commercially shipping products
• Experience with Docker and AWS
• Experience with industrial sensors