Applied Scientist

Job Title: Senior Applied Scientist - Computer Vision & Machine Learning

Location: Brazil

Work Mode: 100% Remote

Employment Type: Independent Contractor (hourly pay, no benefits; candidate responsible for own taxes)

Contract Duration: 6 months, with possibility of extension

Hours: 40 hours per week

About the Role

The Inbound team develops highly scalable solutions to determine item attribute values (such as color, material, and style) and verify merchandise authenticity. 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.

Responsibilities

• Develop 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 company’s intellectual property and technical leadership through patents and publications at top-tier conferences and journals.

Requirements

• 5+ years of industry experience in Computer Vision and applied Machine Learning.
• Master’s 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 Requirements

• PhD 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.

Tech Stack

• Programming Language: Python
• Machine Learning / Deep Learning Frameworks: PyTorch, TensorFlow, Keras, Scikit-Learn
• Scientific Libraries: NumPy, pandas
• Computer Vision & ML Techniques: CNNs, Transformers, GANs
• Experimentation & Automation Tools: Ray Tune, Weights & Biases (W&B), Kubeflow
• Cloud Platforms: AWS, GCP, Azure
• Core Areas: Computer Vision, Machine Learning, Deep Learning, Data Engineering, MLOps, Experiment Design, Feature Engineering, Training & Serving Pipelines, A/B Testing