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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

  • Master’s or PhD degree in Computer Science or related fields
  • 5+ years of industry experience with a Master’s degree or 3+ 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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* Please visit Samsung membership to see Privacy Policy, which defaults according to your location. You can change Country/Language at the bottom of the page. If you are European Economic Resident, please click here.

At Samsung, we believe that innovation and growth are driven by an inclusive culture and a diverse workforce. We aim to create a global team where everyone belongs and has equal opportunities, inspiring our talent to be their true selves. Together, we are building a better tomorrow for our customers, partners, and communities.

* Samsung Electronics America, Inc. and its subsidiaries are committed to employing a diverse workforce, and  provide Equal Employment Opportunity for all individuals regardless of race, color, religion, gender, age, national origin, marital status, sexual orientation, gender identity, status as a protected veteran, genetic information, status as a qualified individual with a disability, or any other characteristic protected by law.

Reasonable Accommodations for Qualified Individuals with Disabilities During the Application Process

Samsung Electronics America is committed to providing reasonable accommodations for qualified individuals with disabilities in our job application process. If you have a disability and require a reasonable accommodation in order to participate in the application process, please contact our Reasonable Accommodation Team (855-557-3247) or SEA_Accommodations_Ext@sea.samsung.com for assistance. This number is for accommodation requests only and is not intended for general employment inquiries.

Average salary estimate

$260000 / YEARLY (est.)
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$240000K
$280000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Machine Learning Model Engineer, SEC

Are you ready to dive into the world of machine learning? Join Samsung Ads as a Machine Learning Model Engineer and become a key player in shaping the future of advertising technology! Located in the heart of Mountain View, CA, we are part of Samsung’s innovative family, giving you the unique opportunity to work on exciting projects that truly make an impact. At Samsung Ads, we believe that machine learning is pivotal in the advertising landscape, and you will spearhead efforts to optimize and innovate our systems by utilizing cutting-edge techniques and proprietary data. Imagine collaborating with a talented team of engineers and researchers to deliver production-grade solutions that are not only scalable but also drive significant business results. You will lead the design, development, and deployment of low-latency machine learning products and optimize existing systems while passionately exploring the latest trends in ML technology. As you communicate with various stakeholders, manage roadmaps effectively, and liaise with our MLOps team, you will ensure our products thrive in a fast-paced environment. This role is not just about technical know-how; it's about creativity and leadership. With a culture that encourages learning and problem-solving, your journey at Samsung Ads is bound to be rewarding. If you have a Master’s or PhD in Computer Science and rich experience in machine learning, we can’t wait for you to join our amazing team!

Frequently Asked Questions (FAQs) for Machine Learning Model Engineer Role at SEC
What are the primary responsibilities of a Machine Learning Model Engineer at Samsung Ads?

As a Machine Learning Model Engineer at Samsung Ads, your primary responsibilities include leading a team to deliver production-grade machine learning solutions, designing and deploying scalable low-latency products, and collaborating with stakeholders to understand business requirements. You'll also optimize existing products, work with MLOps, and research advancements in machine learning technology.

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What qualifications are required for the Machine Learning Model Engineer position at Samsung Ads?

To qualify for the Machine Learning Model Engineer role at Samsung Ads, you need to have a Master’s or PhD in Computer Science or related fields, along with significant industry experience. A solid theoretical background in machine learning, proficiency in ML libraries like TensorFlow, and strong programming skills in Python are essential to shine in this role.

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How does the Machine Learning Model Engineer role at Samsung Ads impact the advertising industry?

The Machine Learning Model Engineer at Samsung Ads plays a critical role in the advertising industry by developing and optimizing machine learning products that enhance advertising strategies. By leveraging unique Samsung data and technology, you'll enable brands to connect with audiences effectively, representing a substantial business impact.

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What kind of projects will a Machine Learning Model Engineer work on at Samsung Ads?

At Samsung Ads, the Machine Learning Model Engineer will work on exciting projects that involve developing new machine learning models, optimizing existing solutions, and creating innovative revenue streams. You’ll have the chance to prototype new features and collaborate with cross-functional teams for real-world applications.

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What is the salary range for a Machine Learning Model Engineer at Samsung Ads in Mountain View, CA?

The salary range for a Machine Learning Model Engineer at Samsung Ads located in Mountain View, CA, is expected to be between $240,000 and $280,000, depending on factors like relevant skills and experience. Additionally, the position offers a comprehensive benefits package including medical, dental, and retirement plans.

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Common Interview Questions for Machine Learning Model Engineer
Can you explain a machine learning project you've worked on and the impact it had?

When answering this question, ensure you detail the project’s scope, your role, the technologies used, and the specific outcomes. Highlight how your contributions led to measurable results to show your impact in the field.

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What machine learning libraries are you proficient in and how have you used them?

Be specific about the libraries you are familiar with, such as TensorFlow or PyTorch, and discuss your experience using them in real projects. Illustrate how these tools enhanced your model's performance and workflow.

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How do you approach optimizing machine learning models?

Explain your methodology for model optimization, which may include adjusting hyperparameters, feature selection, and applying different algorithms. Demonstrate your analytical skills by providing examples of successful optimizations you've implemented in the past.

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What challenges have you faced in machine learning projects and how did you overcome them?

Discuss specific challenges like data quality or model accuracy issues, and narrate how you tackled these problems. This reflects your problem-solving abilities and determination to achieve project goals.

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Can you describe the importance of working with cross-functional teams?

Emphasize the collaborative nature of machine learning projects and how working with different teams (like MLOps or product managers) enhances the overall quality and applicability of your work. Share examples of successful collaborations.

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How do you stay updated with the latest trends in machine learning?

Mention your commitment to continuous learning through academic journals, conferences, online courses, and communities. Highlight any specific resources or networks that you find valuable in keeping your knowledge current.

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What expertise do you have in handling big data tools?

Discuss your experience with big data tools such as Spark or Kafka, emphasizing how you've used them for scalable machine learning solutions. Provide examples of projects where these tools enhanced data processing capabilities.

Join Rise to see the full answer
What is your process for evaluating the effectiveness of a machine learning model?

Describe your evaluation metrics, such as precision, recall, or F1 score, and your approach to testing models against this criteria. Include examples of how evaluation influenced model iterations and improvements.

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How have you contributed to the development of production-grade solutions?

Share relevant experiences where you've taken a project from concept to production, focusing on the steps you took to ensure robustness and scalability. Highlight how this aligns with the responsibilities of a Machine Learning Model Engineer at Samsung Ads.

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Why did you choose to pursue a career in machine learning?

Provide a personal narrative that reflects your passion for technology, data, and innovation. Emphasize your excitement for the potential impact of machine learning in various sectors, particularly in advertising, as this is aligned with Samsung Ads' vision.

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EMPLOYMENT TYPE
Full-time, on-site
DATE POSTED
April 17, 2025

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