Machine Learning Model

6 months ago


Mountain View, United States Samsung Electronics America North America Full time

Samsung Ads is an advanced advertising technology company in rapid growth that focuses on enabling brands to connect with Samsung TV audiences as they are exposed to digital media by using the industry’s most comprehensive data to build the world’s smartest advertising platform. Being part of an international company such as Samsung and doing business worldwide means working on the most challenging projects with stakeholders and teams around the globe.

We are proud to have built a world-class organization grounded in an entrepreneurial and collaborative spirit. Working at Samsung Ads offers one of the best environments in the industry to learn just how fast you can grow, how much you can achieve, and how good you can be. We thrive on problem-solving, breaking new ground, and enjoying every part of the journey.

At Samsung Ads, the Platform Intelligence (PI) team is actively delving into the forefront of deep learning and generative AI techniques, aiming to elevate our current systems/products while charting new revenue paths. Our mission is to represent Samsung's leadership in large-scale machine learning / GenAI products by collaborating with the best and brightest engineers and creating a collaborative environment between industry and academia. As a Machine Learning Research Engineer, you can access unique Samsung proprietary data to develop and deploy a broad spectrum of large-scale machine learning products with real-world impact. You will build Generative AI applications for the Advertising domain to enhance user experiences and create new business opportunities. You will work closely with and be supported by a talented engineering team and top-notch researchers to work on exciting machine learning projects and state-of-the-art technologies. A unique learning culture and creative work atmosphere will welcome you. This is an exciting and unique opportunity to get deeply involved in envisioning, designing, and implementing cutting-edge GenAI products with a fast-growing team.

Responsibilities

  • Build next-generation generative AI-based products to open new business opportunities and transform user experience.

  • Explore and share cutting-edge machine learning technologies for our business use cases.

  • Design and develop advanced deep learning models to improve existing products

  • Create quick prototypes and proof-of-concepts for machine learning product features.

  • Closely work with the machine learning engineering team to deploy new models in production to generate real-world impact.

  • Closely work with university collaborators and external partners to advance our machine learning capabilities.

  • Publish research results in top venues and file patents.

Requirements

  • Master’s or PhD degree in Computer Science or related fields

  • Rich hands-on experience in state-of-the-art large language models (LLMs) and/or diffusion models

  • Solid theoretical background in machine/deep learning and/or LLMs

  • Proficiency in mainstream ML libraries (e.g., TensorFlow, PyTorch, Spark ML, etc.)

  • Extensive programming experience in Python, Go, or other OOP languages

  • Familiarity with data structures, algorithms, and software engineering principles

  • Strong communication and interpersonal skills to drive cross-functional partnerships

  • Publications in top relevant venues (e.g., TPAMI, NeurIPS, ICML, ICLR, KDD, WWW, AAAI, IJCAI, etc.)

Preferred Experience Requirements:

  • Basic knowledge about Amazon Web Services (AWS)

  • Experience with machine learning productization

  • Experience with the advertising industry and real-time bidding (RTB) ecosystem

  • 5+ years of industry experience with a Master’s degree or 3+ years of industry experience with a PhD degree

The salary range for this role, for candidates based in California, is expected to be between $230K ~ $280K. Actual pay will be determined considering factors such as relevant skills and experience, and comparison to other employees in the role.

#LT-JT1



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