Description We are actively seeking a Deep Learning Engineer who can join our team in a remote capacity. You will be instrumental in:
- Model Development: Design, implement, and optimize deep learning architectures for predictive modeling, market forecasting, customer segmentation, and lead scoring to extract actionable insights from complex demographic and behavioral datasets in the senior living industry.
- Data Pipeline Engineering: Build robust, scalable data pipelines for training and inference, ensuring efficient data preprocessing, feature engineering, and model deployment workflows that handle large-scale healthcare and demographic datasets.
- Research & Innovation: Stay current with latest developments in deep learning research, experiment with novel architectures and techniques, and translate cutting-edge academic research into practical solutions for senior living market intelligence.
- MLOps & Production: Deploy models to production environments with monitoring, versioning, and automated retraining capabilities. Collaborate with engineering teams to integrate ML capabilities into customer-facing products and internal analytics platforms.
- Cross-functional Collaboration: Partner with data scientists, product managers, and domain experts to understand business requirements, translate them into technical specifications, and communicate model performance and insights to non-technical stakeholders.
Qualifications
- Experience: 3+ years of hands-on experience developing and deploying deep learning models in production environments. Strong portfolio of ML projects demonstrating technical depth and practical application.
- Technical Expertise: Proficiency in Python and deep learning frameworks (PyTorch, TensorFlow). Experience with cloud platforms (AWS, GCP, Azure), containerization (Docker, Kubernetes), and MLOps tools (MLflow, Weights & Biases, or similar).
- Domain Knowledge: Experience with predictive analytics, consumer behavior modeling, or demographic analysis preferred. Background in market research, business intelligence, or customer analytics is a plus.
- Core Skills: Strong mathematical foundation in statistics, linear algebra, and optimization. Proven experience with predictive modeling, segmentation algorithms, and forecasting techniques. Ability to work with complex demographic and behavioral datasets and optimize model performance for production deployment.
- Communication: Excellent written and verbal communication skills with ability to explain complex technical concepts to business stakeholders and contribute to technical documentation and knowledge sharing.
Join Occulytics and contribute to a dynamic team that drives innovation and delivers substantial impact for the senior living industry through the power of artificial intelligence.