Machine Learning Engineer
- New York, NY, United States
- Chicago, IL, United States
- Boston, MA, United States
- Google Cloud Platform
AcuityMD is seeking a Machine Learning Engineer to build software that changes how the Medical Device industry markets and sells their products. We're looking for a world-class machine learning engineer who has a passion for building scalable machine solutions using technologies such as Python, Spark, Beam, GCP, Airflow, and Tensorflow.
What you'll be doing
- Design, develop and deploy large scale, big data-driven machine learning models that are integrated with key product features. Some examples of potential projects include:
- Our Entity Resolution models combine and deduplicate large healthcare data sets
- An extrapolation model to estimate US procedural volume across payers
- Search relevancy engine that recommends targets and strategies to customers based on internal, external data, and user behavior
- Multivariate testing framework that empirically evaluates the efficacy of product enhancements as quickly as possible.
- Collaborate with Engineering, Product, and Analytics leads to establish analytic standards and platforms that scale and can be leveraged in various initiatives throughout the organization
Communicate complex machine learning solutions, concepts and the results of analyses in a clear and effective manner to business stakeholders and technology leaders to maximize the effectiveness of machine learning initiatives
What we're looking for:
- 5+ years of experience as a Data Scientist, ML engineer, or other analytical role working in healthcare data sets (e.g., claims)
- Experience working in a high-growth startup environment
- Advanced knowledge of a data science toolkit like: Python (sklearn, scipy), Spark ML, TensorFlow
- Experience writing production-ready code and implementing machine learning solutions in production environments.
- Familiarity with workflow orchestration tools like Airflow or Temporal
- Hands-on experience with agile software development, system reliability, and offline/online experimentation.
- Experience with product release processes like automated testing and code reviews.
- Comfort working within a cloud-based infrastructure, ideally GCP.
Nearly 6,000 new medical devices get approved by the FDA every year, adding to the the tens of thousands of products interacting with patients every day.
Medical technology improves and personalizes patient care, but it also brings complexity to healthcare providers, their patients, and the companies that serve them.
AcuityMD brings clarity to the products used on patients, helping medical device companies expand access in their markets.
We use data and software to record how medical devices are used, understand why outcomes vary, and identify opportunities for physicians and sites of care
We value resourcefulness and ability to step up and take on responsibility. Every employee is involved in customer conversations and is dedicated to refining their feedback into a product that our users love.
- Google Cloud Platform
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