The Machine Learning Engineer will collaborate with data scientists and software engineers to develop scalable ML models and frameworks, troubleshoot model performance, and implement infrastructure for model testing and deployment.
Note: At this time, we are not able to offer visa sponsorship. Candidates must be authorized to work in the United States without the need for current or future sponsorship.
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.
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.
Top Skills
Airflow
Apache Superset
AWS
Dask
Docker
Duckdb
Grafana
Lightgbm
Mlflow)
Mlops Tools (Sagemaker
Numpy
Pandas
Polars
Prefect
Python
PyTorch
Scikit-Learn
SQL
Terraform
Xgboost
N1 Health Boston, Massachusetts, USA Office
Boston, Boston, MA, United States, 02110
Similar Jobs
Financial Services
Develop and deploy AI and machine learning solutions, collaborate with teams, analyze data for insights, and mentor junior members.
Top Skills:
Amazon EksAWSBedrockDockerKubernetesMlopsPythonPyTorchPytorch LightningSagemakerScikit-LearnTensorFlow
Financial Services
The Applied AI/ML Engineer will design, develop, and deploy AI and machine learning solutions while collaborating with cross-functional teams to optimize processes and enhance operational efficiency.
Top Skills:
Amazon EksAWSDockerKubernetesPythonPyTorchTensorFlow
Artificial Intelligence • Fintech • Machine Learning • Natural Language Processing • Software • Generative AI
As a Machine Learning Engineer II, you will develop intelligent agent frameworks, design retrieval methods, and optimize machine learning systems for actionable insights. This role emphasizes collaboration and hands-on experience in ML lifecycle management.
Top Skills:
AirflowSparkArizeAWSAws AthenaDeepspeedDglDockerDvcGnnsGrafanaHuggingfaceJenkinsJupyterLabelboxLangfuseLanggraphLightgbmLitellmMatplotlibOpensearchPandasPostgres/PgvectorPydanticaiPythonPyTorchRayS3SklearnSqliteTransformersVllmWeights & BiasesXgboost
What you need to know about the Boston Tech Scene
Boston is a powerhouse for technology innovation thanks to world-class research universities like MIT and Harvard and a robust pipeline of venture capital investment. Host to the first telephone call and one of the first general-purpose computers ever put into use, Boston is now a hub for biotechnology, robotics and artificial intelligence — though it’s also home to several B2B software giants. So it’s no surprise that the city consistently ranks among the greatest startup ecosystems in the world.
Key Facts About Boston Tech
- Number of Tech Workers: 269,000; 9.4% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Thermo Fisher Scientific, Toast, Klaviyo, HubSpot, DraftKings
- Key Industries: Artificial intelligence, biotechnology, robotics, software, aerospace
- Funding Landscape: $15.7 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Summit Partners, Volition Capital, Bain Capital Ventures, MassVentures, Highland Capital Partners
- Research Centers and Universities: MIT, Harvard University, Boston College, Tufts University, Boston University, Northeastern University, Smithsonian Astrophysical Observatory, National Bureau of Economic Research, Broad Institute, Lowell Center for Space Science & Technology, National Emerging Infectious Diseases Laboratories
