Senior Machine Learning Engineer, Knox Cloud Service

2 days ago

Mountain View CA United States Samsung Research America Full time

Lab Summary:

Samsung Knox Cloud Service team focuses on the development and research of large-scale production-level machine learning algorithms, models, and systems and aims at representing Samsung's leadership in large-scale machine learning products. The team productizes a wide range of Machine Learning algorithm from various Samsung Research teams and Research papers including both device and server applications. This is an exciting and unique opportunity for a talented and hard-working machine learning engineer to get involved in envisioning, designing and implementing cutting-edge products with a growing team.

Position Summary:

In this position, you will join a collaborative team of world-class developers/research engineers and have a chance to integrate your innovative solutions into our Security & Intelligence services.

Come join the Samsung Knox Cloud Service team and help us shape the future role of Samsung in the machine learning domain

Position Responsibilities:

  • Design, develop, and productize both device and server-side machine learning solutions for Samsung services
  • Productize machine learning algorithms from Samsung Research teams or Research Papers
  • Create quick prototypes and proof-of-concepts
  • Design experiments, perform evaluations, and apply enhancements to our products
  • Create state of the art ML based security solutions for Samsung devices

Required Skills:

  • Master’s or Ph.D. degree in Computer Science, Statistics, Math, Physics, Mechanical Engineering, or other quantitative fields or equivalent combination of education, training and experience
  • 3+ years’ experience in building machine learning and deep learning-based software solutions
  • Solid theoretical background in deep/machine learning and exceptional hands-on experiences in changing the model source code for optimal performance
  • Hands-on experience withvarious MLs, such as GNN, VAEs and transformer-based models
  • Understanding of GenAI Foundation Models, Vector DB and Graph DB: Leveraging foundational AI models and vector/graph database technologies for advanced AI capabilities
  • Familiar with RAG (Retrieval-Augmented Generation) and model fine tuning: Employing RAG techniques for enhanced AI responses and fine-tuning embedder models for optimal performance
  • Familiar with various quantization techniques including QAT and PTQ
  • Use of Orchestration Tools: Utilizing advanced tools like Langchain, Pydantic and others for efficient AI model management
  • Strong programming skills with Python
  • Exceptional problem-solving and interpersonal skills and proven ability to excel in a fast-paced development team
  • Familiar with Amazon Web Services or Google Cloud Platform
  • Familiar with big data tools, data pipelines, RDBMS and NoSQL databases
  • Experience with security & privacy concepts such as zero trust and differential privacy
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