AI/ML Engineer

Skills

● Strong interpersonal skills and the ability perhaps even a passion to build camaraderie and work effectively on difficult goals with a broad range of business and technical collaborators across cultures and skills. ● Self-awareness to know your own superpower (nobody is great at all things) and the humility to permit others to exercise theirs on a team of accomplished specialists ● Respect and empathy to recognize and support the goals of the company your team and colleagues in ways that build trust for people to feel safe to “disagree and commit” (The Amazon Way) ● A work ethic that doesn’t quit that recognizes that time-to-market is often the only thing that separates teams that win from those that don’t (“No matter how hard you work someone else is working harder.” — Elon Musk) ● Tenacity and a dogged determination to never give up ● Innate hunger to constantly do better and evolve both your work product and yourself (You’re a lifelong learner) ● The courage to move fast break things and ship products that people use (“Real artists ship.” — Steve Jobs) ● Exceptional communication skills characterized by meticulous attention to detail and precision in verbal and written expression. Consistently deliver clear comprehensive and precise information to ensure all team members are aligned and well-informed. Additionally articulate the team's efforts and impact on other teams cultivating close collaboration to achieve company-wide objectives. Education and Experience ● A Master's or PhD degree in Artificial Intelligence Mathematics Statistics Physics Electrical Engineering Computer Engineering or a related field or equivalent work experience. ● 10+ years of relevant experience in machine learning and data science with healthcare AI a plus. ● Proven track record of leading and scaling high-performing data science and machine learning teams and successfully delivering complex impactful projects. ● Real-world work experience in relevant roles in a commercial setting. ● Ideally full life cycle experience with a consumer or patient product that has shipped and achieved meaningful commercial success. ● Preference for candidates with experience in a startup or fast-paced environment as well as exposure to ambient sensing and sensor fusion technologies.

Description

We are seeking an experienced, hands-on Principal Engineer with a strong
background in Machine Learning applied to complex spatial computing, image and
video processing, and visualization applications. In this “team of leaders” role, you
will be an individual contributor and work on the design, development, and
implementation of machine learning models for our radar-based health and safety
platforms. You will also work in a collaborative team environment to help envision,
architect, and prioritize our platform’s artificial intelligence features.
While not mandatory, our ideal candidate would also bring meaningful digital signal
processing experience, ideally in similar image, video, and/or radar data processing
applications.

Responsibilities

• ● Setting the overall strategy and vision for the machine learning and data
• science initiatives in the company. Provide strategic guidance and mentorship
• to the data science and engineering teams.
• ● Hiring, training, and developing team members to foster a culture of
• innovation and excellence.
• ● Collaborating with other department heads, such as product management,
• engineering, and healthcare experts, to align machine learning initiatives with
• company-wide goals.
• ● Building strong relationships with stakeholders and effectively communicating
• the value and impact of the team's work.
• ● Managing the budget and resources for the machine learning and data
• science function. Making strategic decisions on investments in tools,
• technologies, and talent to support the team's objectives.
• ● Staying at the forefront of advancements in machine learning and healthcare
• AI, and actively contributing to the broader scientific community through
• publications, conferences, or industry events.
• ● Representing the company as a thought leader and building strategic
• partnerships with academic institutions, research organizations, or industry
• partners.
• ● Developing and optimizing complex machine learning models, such as CNNs,
• LSTMs, and transformers, to tackle challenging problems and enhance
• system performance and scalability.
• ● Designing and implementing machine learning models for data analysis,
• feature extraction, and classification tasks.
• ● Ensuring real-time performance and resource efficiency by implementing and
• validating algorithms on embedded systems.
• ● Working closely with hardware engineers to optimize machine learning
• models for specific hardware architectures and assisting in system integration.
• ● Conducting performance evaluations and simulations to validate model
• performance and identify areas for improvement.
• ● Collaborating with software engineers to integrate machine learning models
• into software frameworks.
• ● Clearly communicating technical concepts and progress not only within your
• team but also to other teams across the company. Ensuring that all
• departments understand the work of the machine learning team and how it
• aligns with and supports the broader company goals.
• Key Technical Requirements
• To hit the ground running, you are comfortable across the entire engineering life
• cycle from system design to model development to model training to system
• testing and optimization, leading to a successful product launch and ongoing
• improvements. In particular:
• ● Proven industry experience as an AI/ML Engineer, with a focus on radar and
• RF signals, video and image processing, or classification.
• ● Proficiency in implementing signal processing algorithms using programming
• languages such as Python, MATLAB, or C/C++.
• ● Fluency in Python, machine learning frameworks (Pytorch, Tensorflow, etc.),
• data science tools (NumPy/Scikit-learn), and cloud services (Google Cloud
• Platform).
• ● Extensive practical knowledge of Machine Learning techniques for images,
• deep learning network architectures (CNNs, GANs, etc.), regularization, loss
• functions, optimization strategies, etc.
• ● Experience with building and orchestrating multiple models using parallel
• and sequential architectures, tailoring the approach to the specific
• requirements and constraints of the problem at hand.
• ● Solid understanding of software development methodologies and version
• control systems.
• ● Experience with real-time signal processing, DSP platforms, or embedded
• systems.
• ● Strong knowledge of digital signal processing theory and techniques,
• including filtering, modulation, demodulation, and spectral analysis.
• In addition, while not essential, it is a definite plus if:
• ● You have worked with C/C++ for embedded systems
• ● You have proficiency in radar signal processing techniques, DSP algorithms,
• and the entire ML lifecycle
• ● Familiarity with radar principles, systems, and waveforms.
• ● You have experience with one or more of the following: radar-to-image
• projection, image segmentation, video object detection, target detection in
• radar signal
• ● You have expertise in radar signal processing and object detection from RF
• signals, including algorithms such as CFAR, SVD, and other radar signal
• processing techniques.
• ● You have experience implementing and optimizing data augmentation
• techniques (e.g., image flipping, rotation, scaling, filtering, text synonym
• replacement, SMOTE) to enhance model performance and robustness.