Join Aibidia's Research and Development team as a Machine Learning/Ops Engineer. You'll create and expand our range of SaaS solutions, playing a pivotal role in delivering an exceptional product to clients such as Nokia, Dyson, Bridgestone, and Olympus. Your work will help revolutionize cross-border business management.
What You'll Do
- Design, build, and maintain end-to-end machine learning pipelines from data ingestion to deployment and performance monitoring.
- Automate ML workflows including model training, testing, and deployment using CI/CD best practices.
- Manage and optimize infrastructure for model serving using containerization (Docker), orchestration (Kubernetes), and Infrastructure-as-Code tools (e.g., Terraform) across cloud environments.
- Ensure reproducibility, versioning, and traceability of data, features, and models across the ML lifecycle.
- Implement monitoring systems for model performance, including accuracy, latency, data drift, and degradation detection.
- Collaborate with data scientists to transition research prototypes into scalable production-ready services.
- Lead model lifecycle management practices including retraining, rollback strategies, A/B testing, and shadow deployments.
- Ensure compliance with data privacy, security, and governance standards, including responsible AI principles.
What We're Looking For
- ML pipeline orchestration using tools like Airflow, Kubeflow, or Prefect.
- Experience setting up automated testing and deployment (e.g., GitHub Actions, Jenkins, GitLab CI, Azure DevOps Pipelines).
- Proficient with Docker, Kubernetes, Terraform for scalable deployments.
- Experience with MLflow, TensorFlow Serving, TorchServe, or similar.
- Experience setting up observability tools to track model/data drift, latency, and failures.
- Experience with AWS/GCP/Azure, especially their ML tools (e.g., SageMaker, Vertex AI).
Nice to Have
- Knowledge of Kafka, Spark Streaming, or Flink for streaming data processing.
- Experience using Terraform for provisioning.
- Experience managing and deploying large language models or embedding pipelines.
- Experience managing compute/storage costs in cloud-based ML workflows.
Technical Stack
- Docker, Kubernetes, Terraform, Airflow, Kubeflow, Prefect
- GitHub Actions, Jenkins, GitLab CI, Azure DevOps Pipelines
- MLflow, TensorFlow Serving, TorchServe
- AWS, GCP, Azure, SageMaker, Vertex AI
- Kafka, Spark Streaming, Flink
Team & Environment
You will be a key member of the Research and Development team, collaborating to build and scale Aibidia's product suite.
Benefits & Compensation
- A fair share of Aibidia's success, including a competitive compensation and incentive package.
- Flexible working hours with a hybrid working policy.
- Comprehensive healthcare package.
- Genuine drive towards physical and mental wellbeing, with initiatives by an internal organisational health and wellbeing committee.
- Regular team social events including Aibidia's summer and winter parties.
- The latest technology to ensure you can do your best work.
- Performance-based growth as part of the company culture and a designated learning budget for every employee.
- An opportunity to be part of a global, fast-growing SaaS company.
- A non-hierarchical atmosphere and stellar culture at the office.
Work Mode
This is a hybrid role with locations in Finland (Helsinki or Tampere offices) or remote within the UK.
We are committed to fostering an inclusive culture that celebrates diversity.
