Senior Software Engineer, Omada Health

• You are an experienced engineer with a passion for modern data technologies. You excel at solving technical challenges, building scalable systems, and collaborating across teams
• You bring a growth mindset, strong communication skills, and technical expertise that allow you to contribute effectively to complex projects
• 4-6 years of experience in software engineering, focusing on platforms for analytics, data science, and AI
• Strong programming skills in languages such as Python, Java, Scala, or similar
• Experience with AI-specific infrastructure, such as model serving (e.g., TensorFlow Serving), feature stores (e.g., Feast), and experimentation platforms (e.g., MLflow)
• Knowledge of data architectures, including data lakes, warehouses, and real-time processing systems
• Experience with cloud-based data and AI platforms (e.g., AWS, Azure, GCP) and associated tools
• Familiarity with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch) and their integration into production systems
• Understanding of distributed computing technologies (e.g., Spark, Kubernetes) and their applications in data engineering and AI
• Knowledge of MLOps/LLMOps practices and tools for managing AI and data pipelines
• Strong problem-solving skills and ability to work on technical challenges
• Effective collaboration and communication skills to work with cross-functional teams

Desirable

• The Senior Software Engineer for AI and Data Technologies will play a key role in building and enhancing our platform capabilities for analytics, data science, and AI initiatives
• This role focuses on developing scalable, efficient, and robust platforms to support analytics, machine learning, and data-driven decision-making across the organization
• While this role does not involve executing analyses, building machine learning models, or performing data transformations, it is pivotal in creating the technological foundation that enables these functions
• Platform Design and Development: Design and develop scalable, secure, and high-performance AI and data platforms to support analytics, data science, and machine learning initiatives
• Cross-Team Collaboration: Collaborate with analytics, data science, and machine learning teams to understand requirements, implement solutions, and support data-driven decision-making across business units
• Technology Integration and Optimization: Evaluate, integrate, and optimize modern tools, frameworks, and technologies to enhance platform performance, scalability, and cost-efficiency
• Engineering Best Practices: Follow and promote best practices for software engineering, including coding standards, model testing and evaluation, automated CI/CD pipelines for AI/ML workflows, scalable and reproducible deployment strategies, and strict adherence to data security, privacy regulations, and governance policies specific to operationalizing AI
• Technical Leadership and Mentorship: Act as a trusted technical contributor to advanced data platform designs, while sharing knowledge and mentoring team members to foster excellence in AI, data engineering, and machine learning
• Data Ecosystem Evolution: Partner with stakeholders to build and enhance enterprise-grade data and AI infrastructure, supporting advanced analytics, AI/ML enablement, and evolving Omada’s data ecosystem to meet future needs