Occulytics Inc. is an innovative startup on a mission to fundamentally change the senior living industry. They are seeking a Deep Learning Engineer to build and deploy cutting-edge deep learning ...
Occulytics
1 job near Columbus, OH
Occulytics Inc. is an innovative startup on a mission to fundamentally change the senior living industry. They are seeking a Deep Learning Engineer to build and deploy cutting-edge deep learning ...
Full-time
Posted 5 days ago
Job description
Job Summary:
Occulytics Inc. is an innovative startup on a mission to fundamentally change the senior living industry. They are seeking a Deep Learning Engineer to build and deploy cutting-edge deep learning models that transform market intelligence and drive data-driven decision making across the industry.
Responsibilities:
• 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.
• 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.
• 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.
• 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.
• 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:
Required:
• 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.
• 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).
• 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.
• Excellent written and verbal communication skills with ability to explain complex technical concepts to business stakeholders and contribute to technical documentation and knowledge sharing.
Preferred:
• Experience with predictive analytics, consumer behavior modeling, or demographic analysis.
• Background in market research, business intelligence, or customer analytics.
Company:
𝐀𝐛𝐨𝐮𝐭 𝐎𝐜𝐜𝐮𝐥𝐲𝐭𝐢𝐜𝐬 Occulytics provides AI-powered solutions built exclusively for senior living sales and marketing. Founded in 2024, the company is headquartered in Chicago, USA, with a team of 2-10 employees. The company is currently Early Stage.
Occulytics Inc. is an innovative startup on a mission to fundamentally change the senior living industry. They are seeking a Deep Learning Engineer to build and deploy cutting-edge deep learning models that transform market intelligence and drive data-driven decision making across the industry.
Responsibilities:
• 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.
• 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.
• 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.
• 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.
• 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:
Required:
• 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.
• 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).
• 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.
• Excellent written and verbal communication skills with ability to explain complex technical concepts to business stakeholders and contribute to technical documentation and knowledge sharing.
Preferred:
• Experience with predictive analytics, consumer behavior modeling, or demographic analysis.
• Background in market research, business intelligence, or customer analytics.
Company:
𝐀𝐛𝐨𝐮𝐭 𝐎𝐜𝐜𝐮𝐥𝐲𝐭𝐢𝐜𝐬 Occulytics provides AI-powered solutions built exclusively for senior living sales and marketing. Founded in 2024, the company is headquartered in Chicago, USA, with a team of 2-10 employees. The company is currently Early Stage.