A Giants Early Learning Center
Principal Machine Learning Engineer
A Giants Early Learning Center, Boston, Massachusetts, us, 02298
Role: Principal AI/ML Engineer
The Principal AI/ML Engineer will be an individual contributor responsible for designing, developing, and implementing machine learning models for radar-based health and safety platforms. This role involves setting the overall strategy for machine learning and data science initiatives, collaborating with various departments, managing resources, and staying current with advancements in the field.
Key Responsibilities:
Strategic Guidance: Provide mentorship to data science and engineering teams.
Team Development: Hire, train, and develop team members.
Collaboration: Work with other departments to align machine learning initiatives with company goals.
Communication: Build relationships with stakeholders and communicate the team's work effectively.
Resource Management: Manage the budget and resources for the machine learning and data science functions.
Thought Leadership: Represent the company in the scientific community and build strategic partnerships.
Technical Contributions: Develop and optimize machine learning models, ensure real-time performance, and integrate models into software frameworks.
Key Technical Requirements:
Experience: Proven industry experience in AI/ML, especially in radar, RF signals, video, and image processing.
Skills: Proficiency in Python, MATLAB, C/C++, machine learning frameworks (PyTorch, TensorFlow), data science tools (NumPy, Scikit-learn), and cloud services (Google Cloud Platform).
Deep Learning: Extensive knowledge of deep learning architectures (CNNs, GANs), regularization, loss functions, optimization strategies.
Software Development: Solid understanding of software development methodologies and version control systems.
DSP & Embedded Systems: Experience with real-time signal processing DSP platforms, embedded systems, and radar signal processing techniques.
Preferred Qualifications:
Educational Background: A master's or PhD in AI, Mathematics, Statistics, Physics, Electrical Engineering, Computer Engineering, or a related field.
Experience: 10+ years of relevant experience in machine learning and data science, with healthcare AI as a plus.
Leadership: Proven track record of leading and scaling high-performing teams.
Startup Experience: Experience in a startup or fast-paced environment, with exposure to ambient sensing and sensor fusion technologies.
Benefits:
Competitive base salary with performance-based pay.
100% covered medical, dental, and vision benefits.
Unlimited paid time off and other perks.
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The Principal AI/ML Engineer will be an individual contributor responsible for designing, developing, and implementing machine learning models for radar-based health and safety platforms. This role involves setting the overall strategy for machine learning and data science initiatives, collaborating with various departments, managing resources, and staying current with advancements in the field.
Key Responsibilities:
Strategic Guidance: Provide mentorship to data science and engineering teams.
Team Development: Hire, train, and develop team members.
Collaboration: Work with other departments to align machine learning initiatives with company goals.
Communication: Build relationships with stakeholders and communicate the team's work effectively.
Resource Management: Manage the budget and resources for the machine learning and data science functions.
Thought Leadership: Represent the company in the scientific community and build strategic partnerships.
Technical Contributions: Develop and optimize machine learning models, ensure real-time performance, and integrate models into software frameworks.
Key Technical Requirements:
Experience: Proven industry experience in AI/ML, especially in radar, RF signals, video, and image processing.
Skills: Proficiency in Python, MATLAB, C/C++, machine learning frameworks (PyTorch, TensorFlow), data science tools (NumPy, Scikit-learn), and cloud services (Google Cloud Platform).
Deep Learning: Extensive knowledge of deep learning architectures (CNNs, GANs), regularization, loss functions, optimization strategies.
Software Development: Solid understanding of software development methodologies and version control systems.
DSP & Embedded Systems: Experience with real-time signal processing DSP platforms, embedded systems, and radar signal processing techniques.
Preferred Qualifications:
Educational Background: A master's or PhD in AI, Mathematics, Statistics, Physics, Electrical Engineering, Computer Engineering, or a related field.
Experience: 10+ years of relevant experience in machine learning and data science, with healthcare AI as a plus.
Leadership: Proven track record of leading and scaling high-performing teams.
Startup Experience: Experience in a startup or fast-paced environment, with exposure to ambient sensing and sensor fusion technologies.
Benefits:
Competitive base salary with performance-based pay.
100% covered medical, dental, and vision benefits.
Unlimited paid time off and other perks.
#J-18808-Ljbffr