ML Engineer

AI
hybrid/lisbon
About mindmymind

We're a tech company and mobile companion built by a group of friends from different walks of life. We believe self-understanding is the key to a joyful life. Inspired by our own personal struggles we're on a mission to put a companion for self-understanding in everyone's hands. We're a semi-remote company with offices in Lisbon and Copenhagen.

About the role

As a Machine Learning Engineer at mindmymind, you will be a key member of our AI team, primarily responsible for building and maintaining the infrastructure for training, data management, labeling pipelines, and scalable model serving. You will work closely with data scientists and domain experts to set up tools and platforms for efficient data processing and annotation. The role also involves serving and maintaining machine learning models in production environments, ensuring their reliability and scalability. As part of the AI team, you will also play a role in designing and implementing strategies for data exploration, preparation, and modeling.

Key responsibilities
  • Design and implement data pipelines for collecting, processing, and storing datasets
  • Develop and manage data labeling platforms to ensure high-quality training data
  • Optimize and maintain machine learning model training infrastructure and processes, ensuring scalability and efficiency
  • Collaborate with data scientists in EDA, feature engineering and data modeling
  • Implement and maintain MLOps practices for continuous integration and deployment of machine learning models
  • Ensure data security and privacy compliance in line with industry best practices
  • Work with Google Cloud Platform (GCP) services for machine learning workloads
  • Monitor and improve model performance and reliability in production environments
  • Qualifications
  • 3+ years of experience as a Machine Learning Engineer or in a similar role
  • Strong proficiency in Python and experience with machine learning libraries (e.g., TensorFlow, PyTorch, Scikit-learn)
  • Experience with cloud platforms, preferably Google Cloud Platform (GCP). Familiarity in other cloud platforms is also welcome
  • Understanding of containerization and orchestration (Docker, Kubernetes)
  • Experience with data labeling platforms and practices for supervised learning
  • Familiarity with MLOps tools and practices for version control, monitoring, and deployment of models
  • Knowledge in building and maintaining data pipelines using tools like Apache Airflow, Kubeflow, or similar is welcome
  • Strong problem-solving skills and the ability to collaborate effectively in a team environment
  • Proactive and able to manage tasks and drive progress independently
  • Interested?

    If you resonate with the above then we would love to hear from you. We aim to answer to all applicants within 2 weeks. Note that recruitment through agencies is not appreciated. If however, you are looking for your next big move, this is the right place.

    Apply