Machine Learning Model Engineer

Position Summary

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 that we get to work 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.

Machine learning lies at the core of the advertising industry. This is no exception to Samsung Ads. At Samsung Ads, we actively explore the latest machine learning techniques to improve our existing systems and products and create new revenue streams. As a machine learning model engineer of the Samsung Ads Platform Intelligence (PI) team, you will have access to unique Samsung proprietary data to develop and deploy a wide spectrum of large-scale machine learning products with real-world impact. 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 machine learning products with a growing team.

Role and Responsibilities

• Lead a team to deliver production-grade machine learning solutions with notable business impact from end to end
• Design, develop, and deploy scalable low-latency machine learning products
• Communicate with various stakeholders to understand business requirements, manage expectations, and create effective roadmaps
• Closely work with machine learning platform and serving teams to deploy and streamline machine learning pipelines
• Optimize and scale up existing machine learning products
• Closely work with the MLOps team to ensure product health
• Closely work with external partners to introduce new machine learning features and tools
• Research the latest machine learning technologies and keep up-to-date with industry trends and developments
• Create quick prototypes and proof-of-concepts for new features
• Design and implement next-generation machine learning models with advanced technologies

Skills and Qualifications

Experience Requirements:

• Master's or PhD degree in Computer Science or related fields
• 6+ years of industry experience with a Master's degree or 4+ years of industry experience with a PhD degree
• Solid theoretical background in machine learning and/or data mining
• Rich hands-on experience with production-grade machine learning solutions
• Proficiency in mainstream ML libraries (e.g., TensorFlow, PyTorch, Spark ML, etc.)
• Experience with mainstream big data tools (e.g., MapReduce, Spark, Flink, Kafka, etc.)
• Extensive programming experience in Python, Go, or other OOP languages
• Familiarity with data structures, algorithms, and software engineering principles
• Proficiency in SQL and databases
• Strong communication and interpersonal skills to drive cross-functional partnerships

Preferred Experience Requirements:

• Publications in top relevant venues (e.g., TPAMI, NeurIPS, ICML, ICLR, KDD, WWW, AAAI, IJCAI, etc.)
• Basic knowledge about Amazon Web Services (AWS)
• Experience with the advertising industry and real-time bidding (RTB) ecosystem

CALIFORNIA ONLY

Salary Range Pay Transparency: Compensation for this role, for candidates based in Mountain View, CA is expected to be between $240,000 and $280,000. Actual pay will be determined considering factors such as relevant skills and experience, and comparison to other employees in the role. Regular full-time employees (salaried or hourly) have access to benefits including: Medical, Dental, Vision, Life Insurance, 401(k), Employee Purchase Program, Tuition Assistance (after 6 months), Paid Time Off, Student Loan Program (after 6 months), Wellness Incentives, and many more.

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