<p>We are seeking a highly skilled Senior Data Engineer with AI / ML desires to design, build, and scale next-generation data and machine learning infrastructure. This role is ideal for a hands-on technical expert who thrives in building complex systems from the ground up, has deep experience in Google Cloud Platform (GCP), and is excited about stepping into management and technical leadership. You will work across engineering, data science, and executive leadership teams to architect cloud-native solutions, optimize real-time data pipelines, and help shape our long-term AI/ML engineering strategy.</p><p><br></p><p><strong>Key Responsibilities</strong></p><p><strong>Cloud & Platform Engineering</strong></p><ul><li>Architect, build, and maintain high-performance data and ML infrastructure on GCP using best-in-class cloud-native tools and services.</li><li>Lead the design of scalable cloud architectures, with a strong focus on resilience, automation, and cost-effective operation.</li><li>Build applications and services from scratch, ensuring they are modular, maintainable, and scalable.</li></ul><p><strong>Real-Time & Distributed Systems</strong></p><ul><li>Design and optimize real-time data processing pipelines capable of handling high-volume, low-latency traffic.</li><li>Implement and fine-tune load balancing strategies to support fault tolerance and performance across distributed systems.</li><li>Lead system design for high availability, horizontal scaling, and microservices communication patterns.</li></ul><p><strong>AI/ML Engineering</strong></p><ul><li>Partner with ML engineers and data scientists to deploy, monitor, and scale machine learning workflows.</li><li>Create and maintain ML-focused CI/CD pipelines, model deployment frameworks, and automated testing harnesses.</li></ul><p><strong>Open-Source & Code Quality</strong></p><ul><li>Contribute to and maintain open-source projects, including active GitHub repositories.</li><li>Champion best practices across code reviews, version control, and documentation.</li><li>Establish, document, and enforce advanced testing methodologies, including integration, regression, performance, and automated testing frameworks.</li></ul><p><strong>Leadership & Collaboration</strong></p><ul><li>Serve as a technical leader and mentor within the engineering team.</li><li>Collaborate effectively with senior leadership and executive stakeholders, translating complex engineering concepts into strategic insights.</li><li>Provide guidance and direction to junior engineers, with an eye toward growing into a people leadership role.</li></ul>

<p><strong>Required Qualifications</strong></p><ul><li>Bachelor's Degree from an accredited university. Master's Degree Highly Preferred </li><li>Expert-level experience with GCP, including services such as BigQuery, Cloud Run, Pub/Sub, Dataflow, GKE, and Vertex AI.</li><li>Strong background in cloud architecture and distributed system design (GCP preferred; AWS/Azure acceptable).</li><li>Proven ability to build applications, platforms, and services from scratch.</li><li>Advanced skills in traffic load balancing, autoscaling, and performance tuning.</li><li>Deep experience with real-time data systems, streaming frameworks, and low-latency infrastructure.</li><li>Strong track record of open-source contributions and maintaining GitHub repositories.</li><li>Expertise in testing methodologies across the software lifecycle.</li><li>Excellent communication skills with comfort interacting directly with executive leadership.</li><li>Demonstrated interest or experience in team leadership or management.</li></ul><p><br></p><p><strong>Preferred Qualifications</strong></p><ul><li>Experience with microservices, Kubernetes, and service mesh technologies.</li><li>Familiarity with MLOps tooling and frameworks (Kubeflow, MLflow, Vertex AI pipelines).</li><li>Strong Python, Go, or similar programming expertise.</li><li>Prior experience in fast-growth or startup environments.</li></ul><p><br></p>

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