Remote Machine Learning Engineer (US Based)

Senior Machine Learning Engineer – AI Scheduling & Optimization

Company: Flexzo AI

Department: Product & Engineering

Employment Type: Full-Time

Level: Senior

$130-160K DOE

About Flexzo AI

Flexzo AI is developing innovative AI-powered technology to transform healthcare staffing and workforce management. Our goal is to make healthcare scheduling smarter, faster, and more efficient by helping healthcare organizations optimize staffing, manage clinician availability, fill open shifts, and improve workforce operations.

We are building a next-generation scheduling platform that leverages artificial intelligence, machine learning, and advanced optimization techniques to solve complex healthcare workforce challenges.

Position Overview

Flexzo AI is seeking a talented Senior Machine Learning Engineer to help design, develop, and deploy the intelligence behind our new healthcare scheduling product.

This individual will play a critical role in developing machine learning models, AI-driven scheduling algorithms, predictive analytics, and intelligent automation that improve how healthcare organizations manage their workforce.

The ideal candidate has strong experience building and deploying production machine learning systems, working with large datasets, and developing algorithms that solve real-world optimization problems. Experience with scheduling, workforce management, healthcare technology, or resource allocation is highly desirable.

This is an opportunity to help build a product from the ground up and have a direct impact on the architecture, intelligence, and capabilities of Flexzo's scheduling platform.

Key Responsibilities

AI-Powered Scheduling & Optimization

• Design and develop intelligent scheduling algorithms for healthcare workforce management.
• Build machine learning models to match healthcare professionals with available shifts based on qualifications, skills, availability, location, preferences, and organizational requirements.
• Develop algorithms to optimize shift coverage, minimize scheduling conflicts, and improve workforce utilization.
• Create intelligent systems that can recommend optimal staffing decisions.
• Develop solutions for last-minute callouts, shift cancellations, open-shift coverage, and staffing shortages.
• Explore constraint programming, operations research, mathematical optimization, and reinforcement learning where appropriate.

Machine Learning Development

• Design, train, test, and deploy machine learning models for production applications.
• Develop predictive models for staffing demand, workforce availability, scheduling patterns, and shift-fill probability.
• Build systems that learn from historical scheduling and staffing data.
• Develop recommendation engines and intelligent matching systems.
• Evaluate model performance, accuracy, reliability, and scalability.
• Continuously improve models using real-world feedback and operational data.

AI & Intelligent Automation

• Research and implement emerging AI technologies that improve scheduling and workforce management.
• Leverage large language models (LLMs), AI agents, and other AI capabilities where they provide practical value.
• Build intelligent workflows that automate repetitive scheduling and staffing tasks.
• Integrate AI models and services into Flexzo's scheduling platform.
• Use AI-assisted engineering tools to accelerate development, testing, and experimentation.

Data Engineering & Infrastructure

• Work with engineering to build reliable data pipelines and machine learning infrastructure.
• Process and analyze large datasets related to healthcare staffing, scheduling, clinician availability, and workforce utilization.
• Develop data models and features that support predictive analytics and optimization.
• Establish model monitoring, evaluation, and retraining processes.
• Ensure data quality, model reliability, and production scalability.

Product & Engineering Collaboration

• Work closely with full-stack engineers, product managers, and company leadership.
• Translate business and scheduling challenges into technical machine learning solutions.
• Help define the technical architecture and AI roadmap for Flexzo's scheduling product.
• Collaborate on API development and integration of machine learning models into the product.
• Take ownership of projects from research and prototyping through production deployment.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, Data Science, Mathematics, Statistics, or a related field.
• 5+ years of experience in machine learning, AI engineering, or applied data science, including production deployment experience.
• Strong programming skills in Python.
• Experience with machine learning frameworks such as PyTorch, TensorFlow, or scikit-learn.
• Experience developing, deploying, and maintaining production ML models.
• Strong understanding of algorithms, statistics, optimization, and data structures.
• Experience working with structured data, SQL, and data processing pipelines.
• Experience with cloud-based ML infrastructure such as AWS, Google Cloud, or Azure.
• Ability to translate complex business problems into practical AI and machine learning solutions.
• Strong problem-solving skills and ability to work in a fast-paced product development environment.

Preferred Qualifications

• Experience building scheduling, workforce management, staffing, or resource allocation software.
• Experience with operations research, constraint programming, linear programming, mixed-integer optimization, or scheduling algorithms.
• Healthcare technology or healthcare SaaS experience.
• Familiarity with healthcare workforce data, clinician credentials, specialties, and staffing requirements.
• Experience with recommendation systems, predictive modeling, and optimization engines.
• Experience with LLMs, AI agents, and generative AI applications.
• Familiarity with HIPAA, healthcare data security, and healthcare interoperability standards such as HL7 and FHIR.
• Experience building scalable ML APIs and cloud-based model-serving infrastructure.
• Experience with MLOps, model monitoring, CI/CD, and automated model evaluation.

What Flexzo AI Offers

• Opportunity to build the AI intelligence behind a next-generation healthcare scheduling platform.
• Significant ownership and influence over product architecture and machine learning strategy.
• Opportunity to solve complex, real-world healthcare workforce challenges.
• A collaborative, innovative, and technology-driven startup environment.
• Competitive compensation and potential equity opportunities.
• Opportunity to make a meaningful impact on healthcare operations through AI.

Ideal Candidate

The ideal candidate is a hands-on machine learning engineer who enjoys building practical AI solutions that solve difficult operational problems.

They understand that healthcare scheduling is more than filling open shifts. It requires balancing clinician qualifications, availability, preferences, location, staffing requirements, labor rules, and organizational priorities.

They can take a complex scheduling problem, develop an intelligent solution, and turn it into reliable production software.

Most importantly, they are excited about building something new and helping Flexzo AI create a smarter, more automated future for healthcare workforce scheduling.