ML/MLOps Engineer
Who we are
We're pioneering the way to operate commercial buildings. Since buildings are one of the largest sources of carbon emissions globally, we made it our mission to reduce their environmental impact. Our easy-to-retrofit, cloud and AI-native Building Management Systems (BMS) minimizes heating energy consumption while helping owners cut operational costs and enhance occupant comfort.
We're looking for an ML/MLOps Engineer to join our purpose-driven ETH spin-off-either immediately or by mutual agreement. In this role, your expertise in deploying, operating, and maintaining machine learning services will be instrumental in making our vision becoming reality.
About the job
As an ML/MLOps Engineer, you will be responsible for:
*Designing, building, and maintaining end-to-end ML-pipelines using Kubeflow, ensuring scalability and robustness.
*Implementing advanced testing strategies for ML-pipelines - such as simulation-based testing - to support continous integration and ensure reliability.
*Develop and maintain reliable deployment strategies for ML-pipelines and models (e.g. canary deployment).
*Ensure consistent and reliable model operation across a variety of execution modes: scheduled jobs, integration within constrained optimization frameworks (Model Predictive Control), or real-time inference.
*Implement and manage monitoring solutions to detect model drift, control performance drops, etc. using Grafana and Prometheus.
*Orchestrate and manage containerized ML workloads using Kubernetes and Kubeflow on Google Cloud Platform (GCP).
*Conducting peer reviews of code written by other developers, debugging issues, and optimizing overall platform performance.
What you offer
*Background in Computer Science, Data Sciene, or related technical field.
*5+ years of professional experience in MLOps, with a strong track record of delivering production-grade solutions.
*Proven expertise in deploying and managing machine learning workloads using Kubernetes and Kubeflow.
*Hands-on experience in developing time series ML models, including feature engineering, hyperparameter tuning, and model evaluation in Python
*Experience working with public cloud platforms, particularly Google Cloud Platform (GCP) is an advantage.
*Familiarity with monitoring and alerting tools. Grafana and Prometheus is beneficial.
*Experience with PostgreSQL or similar relational databases is considered a plus.
*Independent work style, hands-on mentality, and strong teamwork skills.
*Fluent in English (at least C1 level) and excellent communication skills in general.
What we offer
*An international, smart, and enthusiastic team with a clear vision.
*A meaningful job in a DeepTech startup committed to sustainability.
*Exciting insights into the rapidly growing and emerging AI industry.
*Short decision paths, flat hierarchies, and the opportunity to shape the company.
*Competitive salary package, including an employee stock option plan (ESOP).
*Hybrid/remote work options and flexible working hours.
*A steep learning curve to accelerate your career and individual training opportunities.
*Regular team events.
