MLOps Researcher

Detalhes da oferta

• Develop and Enhance MLOps Backend:
  • Continue developing our MLOps backend, focusing on security in and scalability;
  • Integrate with tools for experiment tracking and model storage.
• Infrastructure Management:
  • Handle data transfer and metadata storage;
  • Streamline infrastructure configuration and deployment for clients (including Kubernetes clusters).
• Module Registry Development:
  • Contribute to the development of a module registry for Python code modules that integrate with the existing backend.
• Collaboration and Maintenance:
  • Maintain and improve the current codebase;
  • Collaborate with other engineers to further develop the overall platform.

• Academic Qualifications: Master’s degree or equivalent qualifications in Computer Science, Electrical and Computer Engineering, or related studies.
• Technical Skills:
  • Proficient in writing Python code;
  • Experience with microservices and containerization technologies like Docker and Kubernetes (or willingness to learn);
  • General knowledge of machine learning workflows and frameworks (e.g., scikit-learn, TensorFlow, Keras, PyTorch);
  • Experience in cloud computing, particularly AWS;
  • Experience with infrastructure-as-code tools like Terraform;
  • Familiarity with MLOps tools such as Kubeflow, Metaflow, MLFlow, or similar.
  • Knowledge of storage solutions like S3 and MinIO for data transfer and metadata storage.
• Other Skills: Excellent English communication skills (technical and general audiences).

• Expertise in hosting and scaling ML pipelines in production environments;
• Ability to work effectively in multidisciplinary and cross-functional teams;
• Autonomous, dependable, proactive, and a critical-thinking team player.

• Innovative Environment: Be part of a people-centric workplace that fosters creativity and out-of-the-box thinking. We encourage the development of new ideas and ensure that every voice is heard;
• Research with Impact: Engage in projects that sit at the intersection of research and real-world applications, contributing to technology that makes a tangible difference in society;
• Multidisciplinary Teams: Collaborate with professionals from diverse backgrounds, enhancing your learning and professional growth;
• Professional Excellence: Work within a culture that upholds professional standards and best practices, promoting continuous improvement and excellence;
• Flexible Work Arrangements: Benefit from flexible working hours and opportunities to work from home, supporting a healthy work-life balance;
• Comprehensive Benefits: Benefit from a partially funded health insurance plan, and a variety of additional perks;
• Supportive Culture: Join a team with an excellent spirit, where collaboration, mutual support, and team achievements are celebrated.

• Curriculum Vitae (mandatory);
• Motivation Letter;
• Recommendation Letters (optional but welcome).

• ACHILLES – Human-centred Machine Learning: Lighter, Clearer, Safer, with Notice No. HORIZON-CL4-2024-DATA-01-01 and reference XYZ;
• NextGenAI – Center for Responsible AI, with Notice No. 01/C05-i01/2021 and reference Projeto nº 62 - C645008882-00000055.