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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning Engineer - Remote - **Company:** TOWN'S EDGE CAR WASH, INC. - **Location:** United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Big Data, Software as a Service, Cloud Computing, Computer Programming, Continuous Integration, Data Structures, Monitoring of Systems, Interoperability, Python (Programming Language), Linear Programming, Machine Learning, Operational Data Store, Recommender Systems, Tensorflow, Software Deployment, SQL Databases, Reinforcement Learning, Google Cloud, Pytorch, Fast Healthcare Interoperability Resources, Large Language Models, Model Validation, Generative AI, Agentic-AI, Scikit Learn, Information Technology, Health Level Seven International, Build Tools, Machine Learning Operations, Api Design, Data Pipelines, Scheduling Algorithms - **Published:** November 13, 2026 - **Apply:** https://arc.dev/remote-jobs/j/redirect/pz6vdp4l09 ## About the Role 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., * 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., * 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. ## Description 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., * 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.