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Principal Machine Learning Engineer
2 months ago
Job Title: Principal / Director Machine Learning Engineer
Location: United States
About Us: Join a leading organization at the forefront of innovation in AI, machine learning, and signal processing technologies. We are dedicated to pushing the boundaries of technology in radar and RF signals, video and image processing, and real-time embedded systems. Our work impacts industries ranging from defense to consumer electronics, and we're seeking a visionary Principal or Director-level Machine Learning Engineer to lead our cutting-edge projects.
Role Overview: We are looking for a seasoned Principal / Director Machine Learning Engineer with over 10 years of experience in radar and RF signals, video and image processing, or classification, along with deep expertise in real-time signal processing and embedded systems. In this role, you will drive the design, development, and deployment of advanced machine learning models and algorithms that process complex signals and images in real-time environments.
Key Responsibilities:
- Lead Innovation: Spearhead the development of novel machine learning algorithms and models for processing radar, RF signals, and video/image data, ensuring they meet real-time performance requirements.
- Technical Leadership: Provide strategic technical direction and mentorship to a team of machine learning engineers, ensuring alignment with organizational goals.
- Cross-Disciplinary Collaboration: Collaborate with hardware engineers, software developers, and data scientists to integrate machine learning models into embedded systems.
- Project Management: Oversee the full lifecycle of machine learning projects, from research and prototyping to deployment and optimization, ensuring timely delivery and high-quality results.
- Research & Development: Stay abreast of the latest advancements in machine learning, signal processing, and embedded systems, driving innovation and the adoption of best practices within the team.
- Performance Optimization: Optimize models for real-time processing and deployment in resource-constrained environments, ensuring robust and efficient operation.
- Stakeholder Engagement: Communicate complex technical concepts to non-technical stakeholders, providing clear and actionable insights to drive business decisions.
Qualifications:
- Experience: 10+ years of experience in machine learning, with a strong focus on radar and RF signals, video and image processing, classification, real-time signal processing, and embedded systems.
- Education: Advanced degree (Master’s or PhD) in Computer Science, Electrical Engineering, or a related field.
- Technical Expertise: Proficiency in machine learning frameworks (TensorFlow, PyTorch, etc.), signal processing techniques, and programming languages such as Python, C++, or MATLAB.
- Embedded Systems: Extensive experience in developing and deploying machine learning models on embedded platforms.
- Leadership: Proven track record of leading teams, managing complex projects, and delivering results in a fast-paced, high-tech environment.
- Communication Skills: Excellent verbal and written communication skills, with the ability to effectively convey complex ideas to both technical and non-technical audiences.
- Problem-Solving: Strong analytical and problem-solving skills, with the ability to navigate and resolve complex technical challenges.
Preferred Qualifications:
- Familiarity with FPGA development and implementation.
- Experience with cloud-based platforms and edge computing solutions.