About Spatialise:
Spatialise is a dynamic Dutch startup founded in 2021, which is leading the way in digital soil health monitoring. As a pioneering start-up, we focus on harnessing remote sensing to empower farmers worldwide, helping them adapt to increasing pressures from global population growth and evolving legislation. Our mission extends beyond commercial success—we are committed to promoting sustainable, regenerative agricultural practices that enhance soil health and reduce pressure on our precious soils. Our product enables project developers, large corporations and NGOs with a scalable solution to measure and quantify the impact of their regenerative agricultural practices on soil nutrient levels.
About the Role:
The MLOps/ML Engineer role is pivotal in ensuring the seamless integration and operational efficiency of machine learning models within our organization. This position demands a blend of skills in environment management, data handling, code integration, and model management. The ideal candidate will have hands-on experience deploying and managing environments using Docker and Kubernetes, as well as overseeing compute resources to optimize deployment costs. A critical part of this role involves implementing and maintaining deployments on cloud platforms such as Databricks, ensuring our ML models are scalable, reliable, and effectively integrated into our workflows.
In addition to environment management, the MLOps/ML Engineer will oversee data ingestion from various databases, implementing robust data lineage and feature engineering practices to maintain data integrity and traceability. The candidate will be responsible for developing and maintaining CI/CD pipelines, enforcing version control, and conducting thorough code reviews to ensure high-quality, reproducible code. Furthermore, the role involves the deployment, monitoring, and retraining of machine learning models, managing ML model endpoints, and creating internal dashboards to monitor performance. Collaboration is key, as the engineer will work closely with full-stack developers and AI scientists to integrate and optimize ML solutions, contributing to the continuous improvement of our machine learning operations.
Key Responsibilities:
Environment Management:
Deploy and manage environments using Docker and Kubernetes.
Manage compute resources and control deployment costs.
Implement and maintain deployments to cloud platforms like Databricks.
Data Handling:
Oversee data ingestion from various databases.
Implement data lineage and feature engineering practices.
Ensure data cleanliness and consider the integration of data streaming processes.
2. Code Integration and Management:
Develop and maintain CI/CD pipelines across development, testing, and production environments.
Enforce version control and conduct code reviews to ensure reproducibility and quality.
3. Model Management:
Handle the deployment, monitoring, and retraining of machine learning models.
Manage ML model endpoints and internal dashboard creation.
4. Inference and Optimization:
Develop APIs for model inference and optimize machine learning services for performance and scalability.
5. General Operations:
Construct and maintain efficient pipelines and automate permission management.
6. Collaboration:
Work closely with our full-stack developers and AI scientists to integrate and optimize ML solutions.
Ideal Candidate:
Technical Expertise:
Proficient in Kubernetes (K8S) and familiar with Python, PyTorch, and MLFlow.
Strong experience in cloud platforms, particularly Azure and Databricks.
Solid understanding of MLOps or DevOps principles with a minimum of 5 years of relevant experience.
Proven ability to establish and maintain MLOps pipelines.
Experienced in managing multiple environments.
2. Personal Qualities:
Strong problem-solving skills and the ability to work in a dynamic, fast-paced environment.
Excellent communication skills and the ability to collaborate effectively with cross-functional teams.
Detail-oriented with a passion for technology and continuous learning.
Intra- and entrepreneurial skills. Ability to challenge yourself to the next level.
Unique opportunity to join the team that encourages people to implement their skills, passions and abilities to the fullest.
Our offer:
A short recruitment process: offer in two meetings!
60k to 75k EUR/yearly.
28 days of paid vacation.
0.8 FTE - 1.0 FTE, unlimited contract.
Employee stock options: take part in our success.
Accommodating employment conditions.
