Conviva is the intelligence layer for digital businesses, turning every consumer interaction into outcome-based intelligence—linking engagement patterns across AI agents, apps, websites, and streaming video to real results
As a Senior Machine Learning Engineer, you will play a key role in advancing our AI initiatives and contributing to the development of our Real-Time Performance Analytics Platform. You will work across a broad range of ML technologies to create innovative, customer-focused solutions.
In this role, you'll collaborate closely with vertical product teams to design and deploy ML models directly within product pipelines. You'll work with other team members to build scalable ML tooling and infrastructure, combining research, product integration, and data development.
What Success Will Look Like:
Design, develop, and deploy machine learning models that power AI-based features across a large-scale data analytics platform. Own ML systems end-to-end, from data ingestion and feature engineering to training, deployment, monitoring, and iteration in production environments. Build and maintain ML infrastructure and MLOps pipelines for scalable, repeatable model development and deployment. Collaborate with infrastructure and backend engineers and product teams to ensure ML solutions are aligned with platform performance and user needs. Continuously evaluate model performance using robust testing, monitoring, and alerting systems for data and model drift. Identify opportunities to improve system robustness and proactively detect data, device, or user level anomalies through intelligent alert mechanisms. Drive technical decisions, code quality, and best practices for ML engineering within a small, high-impact team. Who You Are and What You've Done:
PhD in Computer Science, Machine Learning, or a related technical field; OR a Master's degree in Computer Science or Machine Learning with 2+ years of experience in machine learning engineering or a related field. Proven track record of owning the ML lifecycle: data pipelines, model training, validation, deployment, monitoring, and optimization. Strong software engineering background with 5+ years of experience and proficiency in modern languages like Python, Rust, Java, or Scala. Experience with big data frameworks (e.g., RAY, Spark, Flink) and ML infrastructure (e.g., MLflow, Kubeflow, or custom pipelines). Strong cross-functional collaboration skills and a bias toward proactive problem-solving, continuous improvement, and system-level thinking. What Would Make You Stand Out (Bonus Points):
Experience with real-time data processing and analytics. Familiarity with time series analysis and forecasting techniques. Background in building AI-powered alerts, anomaly detection, or similar AI driven applications. Familiarity with cloud-based ML deployment and MLOps best practices. * This position will be based in our Foster City, CA office.
The expected salary range for this full-time position is $180,000 - $220,000 + equity + benefits. The actual level and compensation are determined by several factors, such as your qualifications, professional background, and relevant experience.
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