Staff Software Engineer, Omada Health

• You are a visionary engineer and trusted advisor with expertise in modern data technologies
• You enjoy tackling ambiguous, high-impact problems and proactively influencing technical and strategic decisions
• Your ability to mentor others, communicate effectively, and lead complex projects sets you apart
• 8+ years of experience in software engineering, with a focus on building platforms for analytics, data science, and AI
• Strong programming skills in languages such as Python, Java, Scala, or similar
• Experience with AI-specific infrastructure, including model serving (e.g., TensorFlow Serving, NVIDIA Triton), feature stores (e.g., Feast, Hopsworks), and experimentation platforms (e.g., MLflow, Kubeflow)
• Expertise in designing and implementing 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 environments
• Knowledge 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
• Demonstrated ability to lead technical projects from concept to delivery
• Excellent problem-solving skills and ability to navigate complex technical challenges
• Strong collaboration and communication skills to work effectively with cross-functional teams

Desirable

• The Staff Software Engineer for AI and Data Technologies will play a critical role in advancing our platform and enablement capabilities for analytics, data science, and AI initiatives
• This role is focused on designing and building scalable, efficient, and robust platforms and architectures to support analytics, machine learning, and data-driven decision-making across the organization
• While the role is not responsible for executing analyses, building machine learning models, or performing data transformations, it is instrumental in creating the technological foundation that empowers these functions
• Strategic Platform Leadership: Drive the design, development, and deployment of scalable AI and data platforms. Focus on building and maintaining reliable infrastructure for analytics and AI/ML workloads, leveraging best practices in MLOps/LLMOps, automation, and cloud-native technologies to support Omada’s business needs
• Enterprise Data & AI Architecture: Architect and implement robust, secure, and high-performance systems for data ingestion, storage, processing, and model lifecycle management. Ensure platforms are optimized for scalability, reliability, monitoring, and future-proofing, with a strong emphasis on automation
• Cross-Functional Enablement: Collaborate with analytics, data science, and machine learning teams to anticipate challenges, align on requirements, and ensure platforms enable data-driven decision-making across the organization
• Technology Vision and Optimization: Evaluate, adopt, and integrate state-of-the-art tools, frameworks, and technologies to optimize platform performance, scalability, and cost-efficiency while setting the technical vision for data ecosystems
• Mentorship and Technical Excellence: Provide leadership and mentorship to engineers across teams, fostering skill development in AI and data enablement, while promoting a culture of innovation, collaboration, and engineering excellence
• Governance and Best Practices: Establish and enforce best practices for platform engineering, including data security, privacy, compliance, and governance standards. Drive continuous improvement in deployment strategies, monitoring, and incident response processes.