Principal Data Engineer, Machine Learning

Summary

Join SmithRx, a rapidly growing Health-Tech company, as a Principal Machine Learning Engineer. You will lead ML innovation and technology strategy for modern data platforms, developing and deploying machine learning models for anomaly detection and predictive insights. This key role requires 12+ years of experience in data engineering or a similar field, expertise in data architecture and database design, and proficiency in various programming languages and ML frameworks. You will collaborate with cross-functional teams and provide technical leadership. SmithRx offers competitive wellness benefits, flexible spending accounts, retirement savings, paid time off, and professional development opportunities.

Requirements

• BS, MS, or PhD in Computer Science, Information Systems, or a related field, with 12+ years of experience in data engineering, data science, or a similar role
• Strong expertise in data architecture, database design, and optimization, with experience in OLTP, OLAP, NoSQL, and cloud-based data warehouses (e.g., AWS Snowflake, PostgresDB, DymanoDB, etc)
• Proficiency in programming languages such as Python, and SQL, and tools like Spark, PySpark, Airflow, DBT, Snowflake, Cortext, OpenAI, and Terraform
• Proficiency in machine learning frameworks and libraries such as TensorFlow, scikit-learn, or PyTorch, with hands-on experience in building and deploying machine learning models in production. Track records in developing and deploying ML models, preferably within the healthcare or related industries
• Ability to lead cross-functional teams, influence stakeholders, and manage complex projects in a fast-paced environment
• Strong analytical and problem-solving skills, with the ability to handle evolving requirements and ambiguous challenges
• Excellent communication and presentation skills, capable of conveying complex technical concepts to both technical and non-technical audiences

Responsibilities

• Develop strategies across the entire AI/ML project lifecycle. This includes seamless integration with data platforms, spanning from problem definition and data preparation to model deployment and performance monitoring
• Design, develop, and deploy machine learning models that drive anomaly detection, and predictive insights, leveraging data from our enterprise data warehouse ecosystems
• Build data pipelines and ensure scalable, efficient ML pipelines and workflows for the entire model lifecycle, from problem definition and data preparation to model deployment and monitoring
• Maintain a focus on data quality, security, and compliance in all AI/ML initiatives, particularly within healthcare
• Provide technical leadership, mentoring, and guidance to team members, establishing and enforcing best practices in data engineering and data science
• Collaborate with product managers, data engineers, and engineer leadership to define use cases and integrate AI models and algorithms into existing systems and applications

Benefits

• Highly competitive wellness benefits including Medical, Pharmacy, Dental, Vision, and Life Insurance and AD&D Insurance
• Flexible Spending Benefits
• 401(k) Retirement Savings Program
• Short-term and long-term disability
• Discretionary Paid Time Off
• 12 Paid Holidays
• Wellness Benefits
• Commuter Benefits
• Paid Parental Leave benefits
• Employee Assistance Program (EAP)
• Well-stocked kitchen in office locations
• Professional development and training opportunities