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PlusAIPosted 3 weeks ago

Software Engineer/Senior Software Engineer, Applied ML & Data Mining

On-siteSanta Clara, California, United States

Full TimeSenior LevelDoctorate Or Professional DegreeMedium

Job Summary

Develop and evaluate machine-learning, data-mining, and computer-vision methods using frameworks like PyTorch or TensorFlow, focusing on experimentation, error analysis, and principled metrics. Drive projects end-to-end with a strong sense of ownership, leveraging foundations in data-centric machine learning such as model uncertainty, embeddings, and similarity search. Improve models through data by training, fine-tuning, or curating datasets, potentially utilizing autonomous driving or robotics contexts. Build production full-stack services including REST APIs and React frontends while managing GPU batch inference at scale with vector databases like Milvus or FAISS. Requires a BS, MS, or PhD in Computer Science or related fields.

Required Qualifications

  • BS, MS, or PhD in Computer Science, Machine Learning, or a related technical field, or equivalent practical experience
  • Hands-on experience developing and evaluating machine-learning, data-mining, computer-vision, or information-retrieval methods with a framework such as PyTorch or TensorFlow, including experimentation, error analysis, and principled metrics
  • Foundations for data-centric machine learning: an understanding of model uncertainty and evaluation, embeddings and similarity search, and how training-data composition shapes model behavior
  • Self-driven with a strong sense of ownership: a quick learner who is eager to take responsibility and drive projects forward end to end

Desired Qualifications

  • Production full-stack experience spanning backend services and REST APIs, relational data modeling and SQL, and modern JavaScript or TypeScript frontend development using React or a comparable framework
  • Experience improving models through data — training or fine-tuning, active learning and data flywheels, hard-example mining, uncertainty or disagreement signals, dataset curation — ideally in autonomous driving, robotics, or perception
  • Experience with embedding and multimodal models (CLIP-style models, VLMs), vector databases (Milvus, FAISS, pgvector), or GPU batch inference at scale

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