Machine Learning Engineer - Remote

About The Company

Flexzo AI is at the forefront of developing innovative AI-powered technology aimed at transforming healthcare staffing and workforce management. Our mission is to enhance healthcare scheduling by making it smarter, faster, and more efficient. We enable healthcare organizations to optimize staffing, manage clinician availability, fill open shifts seamlessly, and improve overall workforce operations. By leveraging artificial intelligence, machine learning, and advanced optimization techniques, we are building a next-generation scheduling platform designed to solve the complex challenges faced by healthcare workforce management today.

About The Role

Flexzo AI is seeking a highly skilled Senior Machine Learning Engineer to join our Product & Engineering team. In this role, you will be instrumental in designing, developing, and deploying the core intelligence behind our innovative healthcare scheduling product. Your work will focus on creating machine learning models, AI-driven scheduling algorithms, predictive analytics, and intelligent automation that enhance how healthcare organizations manage their workforce.

The ideal candidate will have extensive experience building and deploying production-grade machine learning systems, working with large datasets, and developing algorithms tailored to real-world optimization problems. Experience in scheduling, workforce management, healthcare technology, or resource allocation is highly desirable. This role offers the unique opportunity to influence the architecture, intelligence, and capabilities of a product built from the ground up, directly impacting the future of healthcare workforce scheduling.

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.
• Proven 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.
• Familiarity 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 thrive in a fast-paced product development environment.

Preferred Qualifications

• Experience building scheduling, workforce management, staffing, or resource allocation software.
• Knowledge of 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 large language models (LLMs), AI agents, and generative AI applications.
• Understanding of HIPAA, healthcare data security, and 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 pipelines, and automated model evaluation.

Responsibilities

• Design and develop intelligent scheduling algorithms tailored for healthcare workforce management.
• Build machine learning models that match healthcare professionals to 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 capable of recommending optimal staffing decisions.
• Develop solutions addressing last-minute callouts, shift cancellations, open-shift coverage, and staffing shortages.
• Apply constraint programming, operations research, mathematical optimization, and reinforcement learning techniques where appropriate.
• Design, train, test, and deploy machine learning models for production environments.
• Develop predictive models for staffing demand, workforce availability, scheduling patterns, and shift-fill probability.
• Build systems that learn from historical scheduling and staffing data to improve accuracy and efficiency.
• Develop recommendation engines and intelligent matching systems to enhance scheduling decisions.
• Evaluate and ensure model performance, accuracy, reliability, and scalability.
• Continuously improve machine learning models using real-world feedback and operational data.
• Research and implement emerging AI technologies that enhance scheduling and workforce management.
• Leverage large language models, AI agents, and other AI capabilities to add practical value.
• Build intelligent workflows to automate repetitive scheduling and staffing tasks.
• Integrate AI models and services into Flexzo’s scheduling platform.
• Utilize AI-assisted engineering tools to accelerate development, testing, and experimentation.
• Collaborate with engineering teams 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 to support predictive analytics and optimization.
• Establish robust model monitoring, evaluation, and retraining processes.
• Ensure data quality, model reliability, and scalability in production environments.
• Work closely with full-stack engineers, product managers, and leadership to translate business challenges into technical solutions.
• Help define the technical architecture and AI roadmap for the scheduling product.
• Collaborate on API development and integration of machine learning models into the product.
• Take ownership of projects from research and prototyping through to production deployment.

Benefits

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

Equal Opportunity

Flexzo AI is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.