Senior Machine Learning Developer I

Summary

We’re looking for a Senior ML Developer to join our AIOps Platform team. In this role, you will work closely with Data Scientists to take AI/ML solutions to production. You will accelerate the delivery of our core AI services from proof-of-concept to highly available, production-grade. You will bridge the gap between data science and platform operations, applying robust software engineering practices, intent-driven development, and MLOps best practices to ensure our systems are scalable, reliable, and performant.

Key Responsibilities

• Production ML Engineering: Collaborate with data science, platform developers and architects, and other teams to operationalize ML models, LLM / Agentic workflows, and advanced analytics.  
• MLOps & Lifecycle Management: Own the end-to-end ML lifecycle (feature engineering, training, evaluation, deployment). Enforce MLOps best practices including CI/CD, model versioning, reproducibility, and rollout controls.
• Pipeline & Architecture Design: Build real-time streaming pipelines using Apache Beam/Dataflow and design robust event-driven architectures (Kafka/PubSub patterns).
• Design and build high-throughput, low-latency system architectures with strict idempotency and deduplication.
• API & Service Delivery: Lead API and schema design for complex ML-enabled services.
• Quality & Reliability: Instill a strong testing and quality mindset across the team (test-driven development, unit/integration tests, code reviews, security checks). Debug and optimize distributed systems for maximum performance.
• Infrastructure Management: Implement Infrastructure as Code (Terraform/CDKTF) to manage scalable, cloud-native deployments.
  

Critical Qualifications

• Bachelor's degree or higher in Computer Science or Computer Engineering or a related field. Relevant experience may be considered in lieu of a degree. 
• 5+ years of professional software engineering experience, specifically focused on production-grade AI/ML systems.
• Expert-level proficiency in Python software engineering.
• Strong experience with the GCP stack (Vertex AI, BigQuery, Spanner, GKE, GCS, Pub/Sub).
• Deep practical knowledge of MLOps best practices and taking models from proof-of-concept to highly available production services.
• Hands-on experience with real-time data processing (Apache Beam, Dataflow) and event-driven architecture (Kafka, PubSub).
• Proven ability in Infrastructure as Code (Terraform/CDKTF) and cloud-native orchestration (Kubernetes).
• Strong software-testing and quality discipline (unit/integration/end-to-end/functional testing, code review, security checks)
• Hands-on experience with ML frameworks such as PyTorch, scikit-learn, XGBoost, or TensorFlow. 
• Experience with graph databases / Spanner Graph and Graph Neural Networks (GNN)
• Strong communication, analytical, debugging, and cross-functional collaboration skills.
• Ability to write clean, efficient, and reusable code. 
• Plus if you have experience with distributed / federated query engines such as Trino. 

Preferred Qualifications

• Experience with telecom industry data and network architecture.
• Post-secondary degrees or certificates in Statistics, Mathematics, and Data Science.
• Experience deploying secure agentic workflows with cost management and decision traceability. 

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