• Design, build, and maintain the core ML infrastructure, including training pipelines, feature stores, model registries, and model serving infrastructure.
• Develop tools and platforms that streamline model training, evaluation, deployment, and monitoring at scale.
• Collaborate with ML Engineers and DevOps to establish CI/CD workflows for ML models, including validation, versioning, and rollout strategies.
• Optimize performance and reliability of large-scale distributed data processing and model inference systems.
• Establish observability and tracing for ML pipelines to track data drift, model performance degradation, and training anomalies.
• Contribute to security and compliance best practices across ML workflows, including access control and auditability.
• Drive technical decisions around tooling, frameworks, and architecture for our ML platform.‍
• Hands-on experience working with LLMs, including scaling third-party hosted inference services (e.g., OpenAI, Cohere, Anthropic) and building fault-tolerant, production-grade workflows around them.

• 5+ years of experience in software engineering, with at least 2 years focused on ML infrastructure, MLOps, or related systems.
• Strong programming skills in Python, Go, or Java, and experience with containerization (Docker, Kubernetes).
• Deep familiarity with ML infrastructure tools like MLflow, Kubeflow, Metaflow, TFX, SageMaker, or Vertex AI.
• Experience designing and running data pipelines using tools like Airflow, Prefect, or similar orchestration frameworks.
• Hands-on experience with cloud platforms such as AWS, GCP, or Azure, especially in the context of ML workloads.
• Solid understanding of CI/CD principles, especially as applied to machine learning workflows.

• Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.
• Prior experience in observability, telemetry, or real-time data processing.
• Experience in platform engineering with a focus on ML systems.
• Experience deploying models in low-latency or high-throughput production environments.

• Competitive salary and benefits package
• Opportunities for career growth and advancement
• A collaborative and innovative work environment
• Competitive stock option package
• Flexibility with remote work options

If you're excited about building cutting-edge backend solutions and want to contribute to scaling cloud-native applications, we'd love to hear from you. Please submit your resume and a writing sample to careers@observo.ai.