Remote Machine Learning Engineer, Data Acquisition

Description:

• Zus is a shared health data platform aimed at accelerating healthcare data interoperability by providing easy-to-use patient data via API, embedded components, and direct EHR integrations.
• The company was founded in 2021 by Jonathan Bush, co-founder and former CEO of athenahealth, and partners with HIEs and other data networks to aggregate patient clinical history.
• As a Machine Learning Engineer within the Data Acquisition (DA) Team, you will utilize your ML expertise to enhance Zus's capabilities.
• The DA team is responsible for building and maintaining the microservices infrastructure that connects with external health data networks to collect patient information and load it into Zus data stores at high volume.
• You will collaborate with software engineers to develop, deploy, and optimize machine learning solutions that address key business challenges.
• Your responsibilities will include conducting research on new methodologies, developing prototypes, and integrating feedback mechanisms to improve models.
• You will work on delivering CI/CD pipelines and automating workflows for reliable and scalable model operations.
• Key focus areas include algorithm experimentation, evaluation and diagnostics, collaboration for product innovation, model and tooling selection, data readiness, and end-to-end ownership of prototypes.

Requirements:

• You must have 3+ years of experience building and shipping ML models, with hands-on experience in production environments using LLMs or classical NLP methods.
• Experience in partnering with software engineers to ship, monitor, and iterate on models in production is required.
• Proficiency in Python is a must; knowledge of Java or Go is a plus.
• A strong understanding of machine learning frameworks and libraries such as TensorFlow, PyTorch, and Scikit-learn is necessary.
• You should have a solid grasp of classical ML algorithms, including their assumptions, strengths, and failure modes.
• Hands-on experience in designing offline or online experiments, including crafting task-specific metrics and conducting error analysis, is essential.
• Familiarity with cloud services like AWS, GCP, or Azure and distributed computing is required.
• Excellent analytical and problem-solving skills with attention to detail are necessary.
• You should demonstrate curiosity and the ability to learn quickly in unfamiliar domains.
• Strong verbal and written communication skills are required to explain complex ML concepts to diverse stakeholders.
• A demonstrated ability to work effectively in a collaborative team environment is essential.

Benefits:

• The position offers competitive compensation that reflects the value you bring to the team, including a combination of cash and equity.
• Robust benefits include health insurance, wellness benefits, a 401k with a match, and unlimited PTO.
• You will have the opportunity to work alongside a passionate team dedicated to changing the world while having fun.
• Zus encourages candidates from underrepresented backgrounds to apply, emphasizing a focus on active learners and individuals who care about disrupting the healthcare system.