The Senior Machine Learning Ops Engineer at Overstory will design and build the foundations of machine learning operations, ensuring models are reliable, maintainable, and deliver real value to customers.
This role involves architecting end-to-end systems for experiment tracking, data management, and scalable deployment.
As one of the first dedicated MLOps hires, the engineer will have significant ownership and influence over the technical direction, balancing best practices with pragmatic delivery.
Responsibilities include designing, building, and maintaining automated pipelines for training, testing, and deploying ML models, as well as experiment tracking systems for performance metrics, data and model versioning, and documentation.
The engineer will also create processes for the full model lifecycle, including registries, release and rollback strategies, and scalable model serving.
Monitoring and alerting for prediction quality, system health, and cost optimization will also be part of the role.
The engineer will advocate for a balance between MLOps best practices and quick slices of value, aligning technical solutions with customer needs, and ensuring MLOps systems support regulatory, privacy, and security requirements.
Requirements:
Candidates should have 8+ years of experience designing and building production-grade ML pipelines and systems, although those with 5+ years of experience are encouraged to apply if they feel they are strong candidates.
Strong knowledge of experiment tracking, model deployment strategies, data versioning, and monitoring is required.
Experience with ML infrastructure tools such as MLflow, Kubeflow, Airflow, feature stores, and model registries is necessary.
Familiarity with GCP and VertexAI is preferred but not required.
Strong communication skills and the ability to align technical solutions with business goals are essential.
Candidates should be comfortable making architectural decisions and balancing best practices with practical trade-offs.
Benefits:
Employees will be part of mission-driven work that reduces wildfires, protects earthโs natural resources, and helps solve the climate crisis.
The position offers a flexible working environment with a lot of autonomy, allowing employees to build their workdays around their lives.
Additional benefits include a remote working budget, an educational budget, and time to develop new skills.
Employees will be surrounded by a vibrant, smart team that values openness, tolerance, and respect.
The position includes equity and a competitive salary.