Data Scientist

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

📋 Description

• Create and prototype machine learning (ML) and deep learning models, mainly for computer vision applications such as object detection, classification, and tracking.

• Transform business challenges into testable hypotheses and establish proofs-of-concept to confirm them.

• Assess and compare various model architectures and pre-trained models.

• Partner with ML Engineers to scale proven prototypes into production systems and stay involved throughout the deployment process.

• Monitor experiments, oversee model and data versioning, and establish objective evaluation metrics.

• Collaborate with product, engineering, and business teams to translate objectives into actionable ML solutions.

⛳️ Requirements

• Master's degree in Electrical Engineering, Computer Science, or a related quantitative field.

• Practical experience in developing ML and deep learning models, with a focus on computer vision applications.

• Strong expertise in Python and a deep learning framework, such as PyTorch or TensorFlow.

• Experience with computer vision models for object detection, image classification, and tracking.

• Solid understanding of deep learning, traditional computer vision, and classical machine learning.

• Experience in benchmarking, conducting ablation studies, and systematically evaluating competing methods.

• Familiarity with handling large, complex datasets.

• Experience working alongside ML Engineers to transition models into production is a plus.

• Knowledge of Azure, AWS, or GCP for ML training and deployment is a plus.

• Familiarity with Docker and CI/CD pipelines is a plus.

• Experience with Hugging Face Transformers, vision transformers, or self-supervised/representation learning is a plus.

• Exposure to generative AI, including prompt engineering, retrieval-augmented generation (RAG), LLM frameworks, or LLM fine-tuning is a plus.

• Background in gaming, iGaming, e-commerce, or other consumer-facing applications at scale is a plus.

🏝️ Benefits

• Opportunities for both professional and personal growth.

• A collaborative, cross-functional environment with noticeable impact.

• Involvement from research and prototyping all the way to production.

• Work on significant, real-world challenges in computer vision and deep learning at scale.