Machine Learning Engineer in Samsung Ads Project
7 miesięcy temu
About the project
Samsung Ads is an advanced advertising ecosystem, spanning hundreds of millions of smart devices across TV, mobile, desktop, and beyond. The project we are recruiting for is focused on enabling brands to connect with Samsung TV audiences building the world’s smartest advertising platform. We use machine learning algorithms for advertising campaigns to enhance targeting, personalization, and optimization. The goal is to deliver the right message to the right audience at the right time, resulting in higher engagement rates and conversion rates.
Audience building is a crucial aspect of effective marketing, especially in today's digital landscape where targeting specific groups of people is essential for success.
During project on-boarding process you will understand our products and services to easily identify the ideal customer persona, considering factors such as demographics, psychographics, and purchasing power.
Being part of an international company such as Samsung you will get to work on the most challenging projects with stakeholders and teams located around the globe.
You will deeply dive into Samsung Advertising Galaxy working with such exciting domains like bidding, pacing and performance-based advertising, as well as recommendations and churn prediction/prevention.
As a machine learning engineer of the Samsung Ads team, you will have access to unique Samsung proprietary data to address existing product challenges and build end-to-end solutions with real-world impact. You will also work with talented engineers and top-notch machine learning researchers on exciting projects and state-of-the-art technologies.
In conclusion, you will play a crucial role in designing, building, and optimizing ML models and platform that supports the end-to-end ML lifecycle, from data ingestion and preparation to model training, deployment, and monitoring. By contributing to the development of high-quality ML models and platform, you will help to democratize access to ML capabilities, accelerate the pace of ML adoption, and foster collaboration among stakeholders.
Role and Responsibilities
- Develop, test, deploy, and maintain data, scalable low-latency machine learning products and pipelines supporting ML products considering factors such as the nature of the data, the complexity of the problem, and the available computational resources.
- Validate the model's performance on unseen data, ensuring that it generalizes well and does not overfit the training data. Conduct rigorous testing to identify and address potential issues, such as bias or fairness concerns.
- Design and develop the next generation machine learning platform to support thousands of model training pipelines concurrently and thousands of billions of daily batch predictions.
- Research the latest machine learning platform technologies pushing the boundaries of what is currently possible with ML and keep up-to-date with industry trends and developments.
- Experiment with new ML platforms tailored to our environment and create quick prototypes / proof-of-concepts.
- Streamline model deployment, unit testing, integration testing, and stress testing and ensure engineering quality.
- Support automation of the ML pipeline using CI/CD principles, promoting consistency, reproducibility, and agility.
- Work with Data Scientists to introduce new ML platform features, help streamline the model development process, and reduce the lead time for model production.
- Closely work with different internal ML teams (e.g., Data Scientists and MLOps teams) to improve codebase and product health.
- Depending of your skills and experience you will have a chance to technically lead people
Technologies in use
- Python
- TensorFlow
- PyTorch
- AWS
- Spark
- Snowflake
- Snowpark
- Github Actions
- Airflow
- Grafana
Skills and Qualifications
- Degree in Computer Science or related fields.
- At least 2 years of proven industry experience.
- Familiarity with CI/CD (e.g.: Github Actions, Airflow, etc.), ETL or big data tools (e.g., MapReduce, Spark, Flink, Kafka, Docker, Kubernetes, etc.).
- Familiarity with mainstream ML libraries (e.g., TensorFlow, PyTorch, Spark ML, etc.) and/or cloud solutions (e.g.: AWS, Sagemaker, etc.).
- Programming skills in Python, Go or other OOP languages.
- Experience in SQL and databases including SQL query optimization.
- Experience with unit test frameworks.
- Familiarity with data structures, algorithms and software engineering principles.
Nice to have
- At least 5 years of industry experience in designing and implementing machine learning systems.
- Experience with Infrastructure as Code (Terraform), orchestration tools (Airflow, AWS Step/Lambda), building CI/CD pipelines using Github Actions, and real-time monitoring/alerting framework such as Prometheus and Grafana.
- Hands-on experience with machine learning related frameworks (e.g., TensorFlow, PyTorch, model registry, OpenMetadata, ML feature store, etc.).
- Extensive programming experience in Python, Go or other OOP languages.
- Proficiency in SQL and databases and experience with SQL query optimization.
- Extensive experience with Snowflake, Snowpark, and Redis/Aerospike.
- Experience with the advertising industry, recommendation systems or real-time bidding (RTB) ecosystem.
We offer
Team:
- Friendly atmosphere focused on teamwork
- Wide range of trainings and a huge support in developing algorithmic skills
- Opportunity to work in multiple projects
- Working with the latest technologies on the market
- Monthly integration budget
- Possibility to attend local and foreign conferences
- Flexible working hours
- Equipment:
- PC workstation/Laptop + 2 external monitors
- OS: Windows or Linux
Benefits:
- Private medical care (possibility to add family members for free)
- Multisport card
- Life insurance
- Lunch card
- Variety of discounts (Samsung products, theaters, restaurants)
- Unlimited free access to Copernicus Science Center for you and your friends
- Possibility to test new Samsung products
Location:
- Office in Warsaw Spire near Metro station
- Working in a hybrid model: 3 days from the office per week
- Attractive relocation package
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