Staff AI/ML Engineer

This is a fully remote position, open to applicants in Greece.

📋 Description

• Overseeing ML research, experimentation, and development from initial concept to final deployment.

• Creating and applying innovative ML/AI methodologies while remaining updated on the latest research and techniques.

• Designing ML pipelines, training infrastructure, and frameworks for model evaluation.

• Collaborating with diverse teams: Working in close partnership with product managers and other stakeholders to ensure AI/ML solutions meet the organization's goals and objectives.

• Communicating proficiently: Documenting your work clearly and conveying your findings, insights, and recommendations to both technical and non-technical audiences, fostering a collaborative and informed atmosphere.

• Leading ML engineering decisions, including model selection, feature engineering, and optimization strategies.

• Converting academic insights into practical applications.

• Mentoring junior ML engineers and establishing ML best practices across the team.

• Partnering closely with AI Systems Tech Leads to ensure the delivery of optimized AI systems and services to production.

• Upholding data governance and privacy: Implementing processes and methods that ensure data governance, privacy, and security.

⛳️ Requirements

• A relevant undergraduate degree in computer science, engineering, mathematics, or a related field is required.

• An advanced degree in AI/ML or a related area is preferred.

• Over 7 years of experience in ML engineering with proven advanced development or research prowess (including innovative projects, publications, and theses), with at least 1 year of leadership experience guiding technical ML initiatives for a small team.

• Profound understanding of ML fundamentals: deep learning, statistical modeling, optimization, and evaluation methodologies.

• Strong proficiency in Python along with ML libraries (PyTorch, TensorFlow, scikit-learn, Hugging Face).

• Experience with ML experiment tracking, model versioning, and reproducible research practices.

• Capability to translate research papers into functional implementations.

• A solid foundation in software development practices (testing, version control, code review).

• Background in NLP is preferred.

• Familiarity with distributed training, MLOps, and cloud ML platforms is preferred.

• A proven record of research publications or contributions to open-source ML projects is preferred.

🏝️ Benefits

• Health insurance.

• Flexible work arrangements.

• Professional development opportunities.