Machine Learning Engineer
6 days ago
Company Description
Wiznry AI empowers allied healthcare practices with tailored, outcome-oriented AI solutions that blend conversational interfaces and actionable insights. We specialize in revolutionizing patient engagement and optimizing operations via smart, adaptable technology, enabling providers to offer superior care while driving efficiency and sustainable growth
Our architecture leverages advanced AI to automate complex workflows and converts multi-source data into clear, actionable recommendations. With highly scalable systems and seamless integrations into industry-leading platforms, we're redefining what's possible in healthcare operations.
Role Description
As a Machine Learning Engineer, you'll build the predictive intelligence that will further enhance our Patient Engagement and Analytics platform. You'll work across product and engineering teams to deliver scalable, production-grade models that enable reliable, consistent AI features for our customers. This role is both strategic and hands-on: you will influence technical direction, elevate engineering standards, and directly contribute code that drives high-impact product outcomes.
What you will do
- Design, build, and deploy ML and predictive AI solutions that power patient engagement, retention, and operational optimization.
- Translate ambiguous business problems into well-scoped ML architectures and experiments, identifying where ML can create leverage across adjacent product areas.
- Own end-to-end model development—from data exploration and feature engineering to evaluation, deployment, monitoring, and iteration.
- Partner with product teams to embed ML capabilities across the platform and deliver high-impact, cross-functional features.
- Contribute to the evolution of a modern, scalable ML platform that supports rapid experimentation, reproducibility, and reliable productionization.
- Champion engineering excellence through mentorship, code quality, system-level thinking, and the introduction of best practices across the team.
What you will bring
- Expertise in modern ML techniques, including deep learning, transformers/LLMs, classical models, ranking and recommendations, NLP, or reinforcement learning.
- Strong foundation in predictive AI, including recommendation systems, binary/multiclass classification, ranking, relevancy, and evaluation methodologies.
- Experience architecting ML solutions from business requirements and identifying high-leverage opportunities for ML across product areas.
- Track record of measurable business impact, delivering ML systems that materially improve product performance, customer experience, or operational efficiency.
- Hands-on engineering excellence, with fluency in Python and frameworks such as PyTorch or TensorFlow, plus modern software development practices.
- Experience building scalable, reliable production systems, including model deployment, monitoring, retraining pipelines, and CI/CD workflows.
- Proficiency with cloud platforms (AWS or GCP) and container/orchestration tools (Docker, Kubernetes, serverless, etc.).
- Comfort with AI-assisted engineering tools (e.g., Cursor, GitHub Copilot) to accelerate development.
- Bachelor's degree in Computer Science or related field—or equivalent practical experience.
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