Machine Learning Engineer

N1 Health is an AI Platform company that helps healthcare organizations prioritize, action, and maximize patient and member interactions. N1 Health’s market-leading Applied AI Platform provides healthcare companies with pre-packaged models, curated third party data, and a secure and scalable technology platform that enables the deployment of targeted services at the individual, household, and neighborhood level. Data science-driven insights lead to relevant, specific, and help-first interventions that optimally connect individuals to resources based on their specific needs and the capacity of the system.

Only 20% of a person’s health outcomes are driven by their interactions with the health care system, the remaining 80% are driven by external factors. We’re working to empower our customers to utilize data science and digital technologies to better serve their most vulnerable members and patients. We’re passionate, creative, and motivated and looking for team members who are the same. We are enthusiastic learners and believe fundamentally that this is a two-way street - we’ll invest in your learning and growth, just as you’ll advance the company’s mission and support our clients through your work.

Role Overview

We are seeking a skilled and motivated Machine Learning Engineer to join our Software Engineering team. In this role, you will play a crucial part in working alongside data scientists, data engineers, and other software engineers to scale up our ML model development tooling to serve our growing business needs.You will assist our team of data scientists to allow them to develop scalable models independently and that the models can be monitored for performance. This role operates with a high degree of autonomy and an important say in the growth and direction of our engineering group and product strategy.

An ideal candidate has prior experience shipping a model into a production environment end-to-end, comfortably acting as a mixture of software engineer, data scientist and data engineer.

Responsibilities include:

• Work closely with our machine learning and data science teams to understand their requirements and contribute to the development of scalable ML model frameworks.
• Pair with data scientists to troubleshoot model performance issues in terms of both latency and prediction quality.
• Prototype and demo new machine learning tooling functionality for data scientists
• Design, implement, and maintain infrastructure for ML model testing and deployment.
• Leverage cloud platforms and containerization technologies to ensure scalability and flexibility.
• Implement automation processes for seamless integration of ML models into the development pipeline.
• Maintain and extend monitoring solutions to track the performance of ML models in real-time.
• Ensure compliance with industry standards and regulations related to data science and ML.
• Lead the model infrastructure components and prioritization on our product roadmap

Requirements

• 2+ Years of Machine Learning Engineering or MLOps experience
• Bachelor's or Master's degree in Computer Science, Mathematics, or related field.
• Proven proficiency in utilizing MLOps tools (SageMaker, MLflow, etc.) to deploy, monitor, and manage models in production environments.
• Strong proficiency in Python and SQL, with plenty of familiarity using popular libraries for machine learning (e.g. scikit-learn, XGBoost, LightGBM, PyTorch) and data manipulation (e.g. Pandas, NumPy, Polars, DuckDB, Dask).
• Experience applying software engineering best practices to both greenfield and brownfield development (e.g. testing, CI/CD, containerization, observability)
• Excellent technical communication and collaboration skills, with a passion for being at the helm of challenging problems in a fast-paced environment.

The Ideal Fit

• Deep passion for applying cutting-edge machine learning and AI technologies to improve healthcare outcomes and patient experiences.
• A self-starter who thrives in ambiguous, fast-paced environments and takes ownership of solving complex problems end-to-end.
• Prior experience working with healthcare data, predictive models, or clinical workflows is a strong plus.
• Comfortable working in cloud-based environments, with familiarity in AWS services and modern ML tooling.
• Hands-on experience with Infrastructure-as-Code (Terraform), automation, and scripting languages such as Python and Bash.
• Strong skills in data visualization and dashboarding tools (Apache Superset, Grafana) for communicating insights effectively.
• Understanding of CI/CD/CT pipelines, version control (Git), and MLOps best practices.
• ·Familiarity with workflow orchestration frameworks like Airflow or Prefect for managing data and ML pipelines.
• Experience in Natural Language Processing, leveraging Python libraries such as NLTK, spaCy, or Hugging Face Transformers.
• Exposure to the Go programming language for performance-oriented components.
• Knowledge of containerization technologies like Docker for building, packaging, and deploying scalable ML applications.

$95,000 - $170,000 a year

If you are excited about a role but your experience doesn’t seem to align perfectly with every element of the job description, we encourage you to apply. You may be just the right candidate for this, or one of our many other roles.

We celebrate diversity and are committed to creating an inclusive environment for all employees.N1 Health is proud to be an Equal Opportunity Employer. Our vision is to foster an environment in which all N1 Health employees of diverse backgrounds and identities feel supported and empowered through the ongoing development of a shared, inclusive culture. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics.