Offer summary

Qualifications:

3+ years of experience in machine learning with a focus on model development and MLOps., Proficiency in programming languages such as Python, Java, or Go., Strong understanding of machine learning frameworks and libraries like TensorFlow and PyTorch., Bachelor's degree in Computer Science or Statistical Science preferred, advanced degrees are a plus..

Key responsabilities:

Develop, deploy, and optimize machine learning solutions in collaboration with the Data Acquisition team.

Conduct research to explore new methodologies and integrate them into product offerings.

Collaborate with data engineers to build and maintain robust data pipelines ensuring data quality.

Implement and manage MLOps practices to streamline the deployment and maintenance of machine learning models.

Job description

Who we are

Zus is a shared health data platform designed to accelerate healthcare data interoperability by providing easy-to-use patient data via API, embedded components, and direct EHR integrations. Founded in 2021 by Jonathan Bush, co-founder and former CEO of athenahealth, Zus partners with HIEs and other data networks to aggregate patient clinical history and then translates that history into user-friendly information at the point of care. Zus's mission is to catalyze healthcare's greatest inventors by maximizing the value of patient insights - so that they can build up, not around.

As a Machine Learning Engineer within the Data Acquisition (DA) Team, you will play a critical role in bringing your ML expertise to Zus.

The Data Acquisition team is responsible for building and running the microservices based infrastructure which connects with external health data networks to collect information about our patients and load it into the Zus data stores at high volume, as well as supporting those services used by customers and internal stakeholders to request that data. You will be responsible for using your prior experience with large language models (LLMs) and MLOps to develop, deploy, and optimize solutions in collaboration with DA software engineering. You will work closely within this cross-functional team to design, implement, and scale machine learning solutions that address key business challenges.

In your role as a ML Engineer, you will be responsible for conducting research to explore new methodologies and techniques, and integrating them into our product offerings. You will develop prototypes to test and improve upon your innovations and develop feedback mechanisms to improve models with human oversight. You will develop CI/CD pipelines, and automate workflows to ensure reliable and scalable model operations. You will be responsible for presenting your learnings and helping the team leverage these methods and technique

As part of our early team you will focus on:

Product Innovation: engage cross functionally to discover opportunities to innovate better and more cost effective solutions for data collection, scaling, and normalizing.

Continuous Growth: Stay up-to-date with the latest advancements in machine learning and AI and figuring out how to leverage it.

Building the Right Tools: Choose the right LLMs, strategy for deployment and use; and work with the team to use them to make our Data Acquisition technology better.

Data Pipelines and Preparation: Collaborate with data engineers to build and maintain robust data pipelines. Ensure data quality and availability for training and evaluation purposes.

Machine Learning Ops: Implement and manage MLOps practices to streamline the deployment, monitoring, and maintenance of machine learning models in production.

Collaboration: Work closely with software engineers, product managers, and other stakeholders to understand requirements, provide technical expertise, and deliver high-quality solutions.

You're a good fit because you have:

3+ years of experience in machine learning, with a strong focus on model development and MLOps, including a proven track record of working with large language models (LLMs)

Proficiency in programming languages such as Python, Java, or Go.

Strong understanding of machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn).

Experience with MLOps tools and platforms.

Familiarity with cloud services (e.g., AWS, GCP, Azure) and distributed computing.

Excellent analytical and problem-solving skills with a keen attention to detail.

Strong verbal and written communication skills. Ability to explain complex technical concepts to non-technical stakeholders.

Demonstrated ability to work effectively in a collaborative team environment.

It’s a bonus if you have:

Knowledge of natural language processing (NLP) techniques and libraries.

Healthcare experience

Experience developing and even designing software for distributed data pipelines

Bachelor's degree in Computer Science, or Statistical Science preferred, advanced degrees are a plus.

We will offer you…

• Competitive compensation that reflects the value you bring to the team a combination of cash and equity

• Robust benefits that include health insurance, wellness benefits, 401k with a match, unlimited PTO

• Opportunity to work alongside a passionate team that is determined to help change the world (and have fun doing it)

Please Note: Research shows that candidates from underrepresented backgrounds often don’t apply unless they meet 100% of the job criteria. While we have worked to consolidate the minimum qualifications for each role, we aren’t looking for someone who checks each box on a page; we’re looking for active learners and people who care about disrupting the current healthcare system with their unique experiences.

We do not conduct interviews by text nor will we send you a job offer unless you've interviewed with multiple people, including the Director of People & Talent, over video interviews. Job scams do exist so please be careful with your personal information.

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