Our parent company, Compact Information Systems LLC, is considered a pioneer of the data industry and was originally founded in 1988 as a mailing list company for direct marketers and print shops. Thirty-five years later, and combining the strength of our sister brands – AccuData Integrated Marketing, AlumniFinder, ASL Marketing, College Bound Selection Service (CBSS), Deep Sync Labs and HomeData – we have grown to become some of the foremost data suppliers in the U.S.
Today, we are Deep Sync. A company that powers agencies and brands with unmatched audience insights, unsurpassed reach, and unrivaled expertise by combining the industry’s most comprehensive data with easy-to-activate solutions. We provide billions of privacy-first data connections annually to thousands of customers. Learn more about us here.
Position Overview
We are seeking a talented and driven Machine Learning Engineer to join our innovative team. In this role, you will have the opportunity to design, develop, and deploy cutting-edge machine learning models that drive business value and revolutionize our products and services. You will collaborate with cross-functional teams, including data scientists, software/data engineers, and product managers. The ideal candidate possesses a strong foundation in machine learning algorithms, exceptional programming skills, and a keen eye for data analysis and feature engineering.
Key Responsibilities:
- Design, develop, and deploy machine learning models and algorithms to tackle a wide range of business challenges
- Conduct data exploration, feature engineering, and model selection to optimize performance and accuracy
- Implement and maintain machine learning pipelines, ensuring seamless integration with existing systems
- Monitor and evaluate the performance of deployed models, and continuously iterate and improve them
- Stay up-to-date with the latest advancements in machine learning techniques and frameworks
- Communicate complex machine learning concepts and results to both technical and non-technical stakeholder
- Build and maintain multi agent reinforcement learning models
- Master's or Ph.D. degree in Computer Science, Statistics, Mathematics, or a related field
- Strong understanding of machine learning algorithms, techniques, and frameworks (e.g., supervised learning, unsupervised learning, deep learning)
- Proficiency in Python programming
- Expertise in data preprocessing, feature engineering, and model evaluation techniques
- Experience with big data technologies (e.g., Hadoop, Spark) and cloud computing platforms (e.g., AWS, GCP)
- Excellent problem-solving skills and ability to think creatively to develop innovative solutions
- Strong communication and collaboration skills, with the ability to work effectively in a team environment
Knowledge and Skills:
Deep understanding of machine learning algorithms, including but not limited to:
- Supervised learning algorithms (e.g., linear regression, logistic regression, decision trees, random forests, support vector machines)
- Unsupervised learning algorithms (e.g., clustering, dimensionality reduction, anomaly detection)
- Deep learning architectures (e.g., convolutional neural networks, recurrent neural networks, transformers)
- Reinforcement learning techniques
- Multi Agent Reinforcement Learning Models
Location:
Kirkland, WA (First 6 months in-office; hybrid schedule available thereafter—typically remote on Mondays and Fridays, with Tuesday–Thursday in-office, subject to manager’s discretion).
Registered to do business and willing to consider candidates in the following states; California, Colorado, Florida, Georgia, Missouri, New York, Oregon, South Carolina, Tennessee, Texas, and Washington.
