Full-Time Data Scientist II (Computer Vision & Deep Learning)

We are looking for a Data Scientist II with a focus on computer vision and deep learning to join our AI/ML team. This role is ideal for someone who is ready to take on impactful machine learning problems and grow into a technical contributor on production-facing models. You’ll work on building and optimizing models using CNNs, transformers, and LLMs to support innovative, data-driven solutions across our products.

• Design and develop machine learning models for computer vision tasks such as image classification, object detection, or segmentation.
• Experiment with transformer-based architectures (e.g., ViT, DETR, CLIP) and explore the integration of LLMs in vision or multimodal applications.
• Collaborate with senior scientists and engineers on end-to-end model pipelines; from data preprocessing to training, evaluation, and deployment.
• Analyze large, complex datasets and apply best practices in feature engineering, model tuning, and performance evaluation.
• Write production-quality, well-documented code and contribute to the team’s shared ML infrastructure and tooling.
• Stay up to date with the latest research and bring new ideas to the team through experimentation and applied innovation.

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field with 2–5 years of experience, or a Master’s degree with relevant academic or internship work.
• Proficiency in Python and experience with ML frameworks like PyTorch, TensorFlow, or scikit-learn.
• Hands-on experience with deep learning models, especially CNNs, and familiarity with transformer models in computer vision (e.g., ViT, CLIP, BLIP).
• Solid understanding of supervised learning, model evaluation, and core ML concepts like overfitting, regularization, and transfer learning.
• Experience working with version control (e.g., Git), experimentation tracking, and reproducible ML pipelines.
• Familiarity with cloud platforms (e.g., AWS, GCP) and containerization (e.g., Docker) is a plus.
• Strong communication skills, curiosity, and the ability to work collaboratively in a cross-functional team.

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