Overview:

We are seeking a skilled Machine Learning Engineer to join our in-person team. As a member of our engineering team, you will be deeply involved in the research and development of innovative algorithmic approaches to signals intelligence, playing a pivotal role in the evolution of our products.

Responsibilities:

• Collaborate with company and engineering leadership to define and design experiments.
• Implement and optimize machine learning models tailored for real-time, edge applications.
• Evaluate the effectiveness and accuracy of new and existing models.
• Stay updated with the latest advancements in machine learning and signal processing.
• Translate complex research findings into actionable insights for product development.
• Work closely with the embedded systems team to integrate machine learning models into our products.
• Provide technical guidance and mentorship to junior team members.

Requirements:

• Experience working in laboratory or professional applied research settings.
• Proven experience in machine learning, signal processing, statistical analysis or related areas.
• Strong programming skills in Python, PyTorch, and similar frameworks.
• Familiarity with Linux OS
• Familiarity with embedded systems and edge computing.
• Excellent problem-solving skills and a passion for innovation.
• Strong communication skills, both written and verbal.
• Eligible for United States Security Clearance

Nice-to-Haves:

• Physics or Radio Physics background with experience with modeling physical systems, especially radio propagation
• Information theory or signal processing background with experience modeling statistical characteristics of signals
• Machine Learning or statistical analysis background with experience designing robust experiment and evaluation frameworks.

What We Offer:

• Competitive salary, equity, and benefits package
• Health, dental, and vision coverage
• 401(k) match
• Unlimited PTO
• Daily office-provided lunches in NYC
• Opportunity to work on cutting-edge technology.
• Collaborative and inclusive work environment.
• Professional growth and learning opportunities.