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Lead AI/ML Solutions Architect
2 months ago
Role: Lead AI/ML Solutions Architect
Location: Boston (5 days onsite)
Company Size: 50 Employees | Team Structure: 3 Members
Sector: Healthcare/Medical Device
We are seeking a highly skilled Lead AI/ML Solutions Architect to enhance our organization's capabilities in artificial intelligence and data science. This pivotal role will involve shaping our strategic direction, overseeing the creation of cutting-edge solutions, and ensuring that our initiatives align with the overall objectives of the company.
Key Responsibilities:
- Establish and implement the strategic vision for AI and data science projects, providing mentorship and leadership to the data science and engineering teams.
- Engage in cross-functional collaboration with product management, engineering, and healthcare specialists to ensure that machine learning initiatives meet organizational goals.
- Keep abreast of the latest advancements in AI and healthcare technologies, contributing to the scientific community through research publications and conference presentations.
- Design and refine sophisticated machine learning models (such as CNNs, LSTMs, and transformers) to tackle complex challenges and improve system efficiency.
- Develop and deploy machine learning solutions for diverse applications, ensuring optimal performance and resource utilization. Work closely with hardware engineers for model optimization and system integration.
- Conduct thorough performance evaluations and simulations to validate and enhance model effectiveness.
- Effectively communicate technical concepts and project progress to internal teams and other departments, ensuring alignment with broader company objectives.
Qualifications:
- Over 10 years of demonstrated experience as an AI/ML Engineer, with a focus on radar/RF signals, video/image processing, or classification.
- Proficient in programming languages such as Python, MATLAB, and C/C++, as well as machine learning frameworks like PyTorch and TensorFlow.
- Familiar with data science tools including NumPy and Scikit-learn, along with cloud platforms like Google Cloud.
- Expertise in machine learning and a deep understanding of image processing, deep learning architectures (e.g., CNNs, GANs), and optimization techniques.
- Experience in constructing and managing models utilizing both parallel and sequential architectures.
- Knowledge of real-time signal processing, DSP platforms, or embedded systems, including a solid grasp of digital signal processing principles and methodologies.
Benefits: Comprehensive Medical, Dental, Vision, and 401(k) plans.
Compensation: $185,000 – $250,000 + bonus and stock options.
