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.