Machine Learning Engineer

TapestryHealth; United States; Remote; USD 120,000 - 160,000; Full time

Job summary

TapestryHealth is seeking an experienced Machine Learning Engineer to design, build, and deploy ML solutions in a healthcare context. You will turn data into actionable insights, collaborate with product and engineering teams, and drive data-informed improvements across services and operations.

The role emphasizes end-to-end ML lifecycle, strong statistical foundations, and clear communication to stakeholders while ensuring HIPAA-compliant data handling and robust model monitoring.

Qualifications

• Master's degree in Statistics, Computer Science, or quantitative field.
• 2+ years of healthcare domain experience.
• Proven experience delivering predictive analytics in production environments.
• Proficient in Python, R, SQL or similar scripting languages.

Responsibilities

• Design, develop, and productionize ML solutions.
• Collaborate with product managers, engineers, and stakeholders as ML expert.
• Handle full ML lifecycle: problem definition, data exploration, feature engineering, training, validation, deployment.
• Participate in code reviews, testing, and QA processes.
• Ensure model reliability, monitoring, and compliance with HIPAA.

Skills

Predictive analytics

Machine learning

Natural language processing

Python automation

Data visualization

R

SQL

Python

Education

Master's degree in Statistics/CS or quantitative field

Tools

SPARK

Prefect

Airflow

MLFlow

Kedro

Git

DVC

Job description

POSITION SUMMARY:

TapestryHealth is seeking outstanding candidates with strong predictive analytics, machine learning, natural language processing, python automation, and data visualization, experience. Success in this role requires dedication to excellence in helping TapestryHealth to deliver high-quality care and promote broad adoption of our technology with streamlined, data-informed processes.

We are looking for a Machine Learning Engineer to analyze large data sets to inform improvements in our services and operations using advanced Machine Learning, Large Language Models, AI, and other advanced methods. We will rely on you to build tools and products to extract valuable business insights for both internal users and client users.

In this role, you should be highly analytical with a knack for deriving actionable insights from data and making business processes more efficient. Critical thinking, problem-solving, cross-functional collaboration, and clear communication skills are essential for success in this role.

We also want to see experience with healthcare data and research. Your goal will be to help our company deliver high quality care services with a more efficient and data informed approach.

PRIMARY RESPONSIBILITIES:

• Design, develop, and put in production machine learning (ML) solutions
• Collaborate with product managers, engineers, and other stakeholders as a specialist and subject matter expert in machine learning.
• Work across the complete lifecycle of ML model development, including problem definition, data exploration, feature engineering, model training, validation, and deployment.
• Participate in code reviews, testing, and quality assurance processes.
• Troubleshoot and resolve technical issues related to AI model, integration, deployment and backend services.
• Implement system telemetry, A/B testing and other statistical methods to validate the effectiveness of AI models. Ensure the integrity and robustness of ML solutions by developing automated testing and validation processes.
• Document and communicate development processes, system designs, and architectural decisions.
• Ensure the security and compliance of healthcare data, adhering to HIPAA regulations.

REQUIREMENTS

• Masters degree in Statistics, Computer Science, or relevant quantitative field
• 2 or more years of experience in healthcare domain
• Proven experience as a Data Scientist / Machine learning engineer in delivering high quality data analyses and implementing high quality predictive analytics in production environments
• Proficiency in using scripting languages such as R, SQL or Python
• Proficiency in using big data analytics tools such as SPARK
• Experience with data engineering orchestration tools such as Prefect, or Airflow
• Ability to own the entire machine learning life cycle from design, training, deployment, and monitoring
• Proficient with MLOPS tools such as MLFlow, Kedro
• Adheres to software engineering best practices such as source code version control (GIT), data version control (DVC), and writes clean modular code
• Strong math skills (statistics & linear algebra)
• Problem-solving aptitude
• Excellent communication and presentation skills

PREFERRED SKILLS

• Experience in working with team members to promote ideas, issues, and initiatives within a constructive group framework
• Must always represent the organization in a positive and professional manner
• Ability to organize and prioritize tasks
• Ability to work independently, be attentive to detail and maintain a positive attitude.