Applied Scientist

Applied Scientist - Detalhes da Vaga. ● The Senior Applied Scientist will own the development and deployment of machine learning solutions while influencing the technical direction of the team. ●This role works closely with Tech Leads, Product, and Engineering partners to design and deliver scalable, data-driven solutions. ● The ideal candidate brings deep expertise in Computer Vision and Machine Learning, along with a strong focus on building robust production-ready systems and mentoring team members. ● ResponsibilitiesDevelop and deploy Computer Vision and Machine Learning solutions to solve business problems. ●Maintain clean, efficient, and scalable code that meets industry standards. ●Analyze large datasets to extract actionable insights and support informed decision-making. ●Apply state-of-the-art Machine Learning methodologies and frameworks to develop robust and scalable models. ●Influence technical direction and take ownership of key system components and solutions to ensure business needs are met. ●Collaborate with key stakeholders to develop data-driven solutions and deployable products. ●Mentor team members and help establish domain expertise across the team. ●Contribute to the companys intellectual property and technical leadership through patents and publications at top-tier conferences and journals. ● Requirements5+ years of industry experience in Computer Vision and applied Machine Learning. ●Masters degree or PhD in Computer Science, Machine Learning, Statistics, or a related field, or 8+ years of equivalent industry experience. ●3+ years of experience building, deploying, and managing machine learning and deep learning models in large-scale production environments. ●Deep understanding of Computer Vision and Machine Learning algorithms and techniques, including CNNs, transformers, GANs, optimizers, and regularization, as well as experiment design and best practices such as A/B testing, training and serving pipelines, and feature engineering. ●Extensive experience with scientific Python libraries such as NumPy and pandas, and Machine Learning frameworks including PyTorch, TensorFlow, Keras, and Scikit-Learn. ●Strong data engineering skills and experience working with large-scale datasets. ●Experience with experiment automation frameworks such as Ray Tune, Weights & Biases (W&B), and Kubeflow. ●Experience with cloud technologies including AWS, GCP, or Azure. ●Fluency in Python. ● Preferred RequirementsPhD preferred in Computer Science, Machine Learning, Artificial Intelligence, Statistics, Operations Research, or a related field. ●Background applying Machine Learning techniques to solve real-world business problems in the retail sector. ●Familiarity with MLOps tools and pipelines. ●Impact-focused mindset with a passion for delivering high-quality models. ●. Requisitos para participar do processo. ● . O que oferecemos.