Job Description
Principal ML/AI Engineer
Location:
Boston (5 days onsite) Employees:
50 |
Team Size:
3 Industry:
Healthcare/Medical Device Seeking a Principal Machine Learning & Data Science professional to be responsible for advancing the company’s AI and data science capabilities. Your role involves shaping strategy, guiding the development of innovative solutions, and ensuring alignment with broader company goals. Most Important Responsibilities:
Define and execute the vision for machine learning and data science initiatives. Provide mentorship and strategic direction to the data science and engineering teams. Collaborate cross-departments working with product management, engineering, and healthcare experts to align machine learning projects with company objectives. Stay updated on the latest developments in machine learning and healthcare AI. Contribute to the scientific community through publications and conferences. Design and optimize complex machine learning models (e.g., CNNs, LSTMs, transformers) to solve challenging problems and enhance system performance. Develop and deploy machine learning models for various tasks, ensuring real-time performance and resource efficiency. Collaborate with hardware engineers for model optimization and system integration. Conduct performance assessments and simulations to validate and improve model efficacy. Clearly articulate technical concepts and progress to internal teams and other departments, ensuring alignment with broader company goals. What You Can Bring to the Table:
10+ years of proven background as an AI/ML Engineer, particularly in radar/RF signals, video/image processing, or classification. Skilled in Python, MATLAB, C/C++, and machine learning frameworks (e.g., PyTorch, TensorFlow). Familiarity with data science tools like NumPy and Scikit-learn, and cloud platforms such as Google Cloud. Machine Learning Expertise and deep understanding of image processing, deep learning architectures (e.g., CNNs, GANs), and optimization strategies. Experience with building and managing models using parallel and sequential architectures. Experience with real-time signal processing, DSP platforms, or embedded systems, including knowledge of digital signal processing theory and techniques. Benefits:
Medical, Dental, Vision, 401(k) Compensation:
$185 – 250K + bonus/stock potential
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Boston (5 days onsite) Employees:
50 |
Team Size:
3 Industry:
Healthcare/Medical Device Seeking a Principal Machine Learning & Data Science professional to be responsible for advancing the company’s AI and data science capabilities. Your role involves shaping strategy, guiding the development of innovative solutions, and ensuring alignment with broader company goals. Most Important Responsibilities:
Define and execute the vision for machine learning and data science initiatives. Provide mentorship and strategic direction to the data science and engineering teams. Collaborate cross-departments working with product management, engineering, and healthcare experts to align machine learning projects with company objectives. Stay updated on the latest developments in machine learning and healthcare AI. Contribute to the scientific community through publications and conferences. Design and optimize complex machine learning models (e.g., CNNs, LSTMs, transformers) to solve challenging problems and enhance system performance. Develop and deploy machine learning models for various tasks, ensuring real-time performance and resource efficiency. Collaborate with hardware engineers for model optimization and system integration. Conduct performance assessments and simulations to validate and improve model efficacy. Clearly articulate technical concepts and progress to internal teams and other departments, ensuring alignment with broader company goals. What You Can Bring to the Table:
10+ years of proven background as an AI/ML Engineer, particularly in radar/RF signals, video/image processing, or classification. Skilled in Python, MATLAB, C/C++, and machine learning frameworks (e.g., PyTorch, TensorFlow). Familiarity with data science tools like NumPy and Scikit-learn, and cloud platforms such as Google Cloud. Machine Learning Expertise and deep understanding of image processing, deep learning architectures (e.g., CNNs, GANs), and optimization strategies. Experience with building and managing models using parallel and sequential architectures. Experience with real-time signal processing, DSP platforms, or embedded systems, including knowledge of digital signal processing theory and techniques. Benefits:
Medical, Dental, Vision, 401(k) Compensation:
$185 – 250K + bonus/stock potential
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