Senior Machine Learning Engineer


 170k - 180k
 United States  (Boston, MA)
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The Senior Machine Learning Engineer will be responsible for designing, implementing, and deploying machine learning models and algorithms that enable our medical devices. The ideal candidate should have a deep understanding of machine learning techniques, strong programming skills, and experience working with large datasets. The Senior Machine Learning Engineer will work closely with cross-functional teams including product management, software engineering, and clinical to deliver high-quality machine learning solutions.

Who We Want

  • Tenacious talent. Results-oriented individuals who create a track record of success. 
  • Curious and passionate people. Zealous about understanding the market to create momentum and secure engagement.
  • Team-oriented mindsets. Our business model requires collaboration and cross-functional partnerships. 
  • Commitment. What we get done today affects the future greatly. Patients are waiting.

What You Will Do

  • Develop, test, and deploy machine learning models and algorithms
  • Collaborate with product management, software engineering, and clinical teams to understand customer requirements and translate them into machine learning solutions
  • Design and implement data processing pipelines for large-scale datasets
  • Research and implement new machine learning techniques and algorithms
  • Conduct experiments and perform statistical analysis to evaluate model performance
  • Optimize model performance and scalability for deployment in production environments
  • Work closely with software engineering teams to integrate machine learning models into our products
  • Participate in code reviews, design discussions, and contribute to the development of best practices for machine learning engineering
  • Other responsibilities as needed

What We Require

  • Master's or Ph.D. degree in Computer Science or Electrical Engineering
  • 5+ years of experience in machine learning engineering or related fields
  • Strong programming skills in Python and familiarity with relevant machine learning libraries such as Sklearn, TensorFlow, Keras, or PyTorch
  • Experience with data preprocessing, feature engineering, and model selection
  • Experience with cloud computing platforms such as AWS or GCP

What You Need to Succeed

  • Excellent communications skills: written, verbal, and interpersonal
  • Strong analytical and problem solving skills
  • The ability to work in a fast paced, remote, and multi-functional team
  • Place a high value on quality and attention to detail

About Casana

Casana is innovating healthcare delivery with a smart toilet seat that enables effortless, integrated, and consistent in-home health monitoring. The Heart Seat™ captures key clinical values, including heart rate, blood oxygenation, and future clinical measurements such as blood pressure, to assist medical teams with monitoring chronic conditions beyond the four walls of the physician’s office. 

The healthcare system has been searching for this actionable intelligence for decades, and it turns out, we were sitting on a great idea all along. Backed by best-in-class VC’s and led by a CEO who founded and exited a tech unicorn to a successful IPO, Casana is innovating the frontier home-health platform built for ease.


Base salary range of $170,000-180,000 per year. Exact compensation may vary based on skills, experience, and location. Our compensation consists of base salary and equity as well as a generous benefits package. 

Casana provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.

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