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About Our Hiring Partner Our hiring partner combines cutting-edge AI and human creativity to help e-commerce brands unlock value in their messiest customer data.
Think of us as a recycling center for customer retention—sorting the good data from the bad to identify which customers are likely to re-engage and generating personalized messages that reignite their interest.
Position Overview We're seeking an ML/AI Data Engineer to join our growing team and build the foundation of our data and machine learning infrastructure.
This role offers a unique opportunity to design and implement scalable ML-driven data solutions in a fast-paced, results-oriented environment.
You'll work at the intersection of data engineering and machine learning, contributing to the development and deployment of AI models that directly impact our clients' revenue generation.
Your Responsibilities - ML-Driven Data Architecture: Design, build, and maintain scalable data and machine learning infrastructure solutions for storage, processing, and model deployment.
- Data Pipelines & ETL Processes: Develop and manage robust data pipelines to extract, transform, and load data from multiple sources, including e-commerce platforms and email marketing tools, while ensuring data integrity and quality.
- Model Training & Deployment: Collaborate closely with the ML team to support the training, optimization, and deployment of predictive models, ensuring seamless integration with data pipelines.
- Data Governance & Security: Implement data governance practices and ensure compliance with data privacy and security regulations, with a focus on scalable and secure data solutions.
- Process Improvement: Continuously improve data processing, model deployment, and system integration processes, contributing to the overall efficiency and scalability of the platform.
- Innovation & Experimentation: Participate in rapid experimentation and iteration, leveraging AI and machine learning to enhance our customer retention solutions.
Qualifications - Bachelor's or Master's degree in Computer Science, Data Engineering, Machine Learning, or a related field.
- 5+ years of experience building enterprise-grade data and machine learning products, with a strong focus on ML-driven solutions.
- Advanced skills in Python and SQL; experience with additional programming languages like Java, Scala, or Rust is a plus.
- Extensive experience with database technologies (SQL, NoSQL, graph databases, time-series databases) and big data technologies (e.g., Hadoop, Spark).
- Proven track record of designing and implementing ETL processes, data pipelines, and machine learning models.
- Proficiency with cloud platforms (e.g., AWS, GCP) and familiarity with ML frameworks and tools (e.g., TensorFlow, PyTorch).
- Experience integrating data from multiple SaaS APIs, particularly e-commerce and marketing platforms, to support ML model training and deployment.
- Strong understanding of data privacy, security best practices, and compliance with industry standards.
Ideal Candidate - You're passionate about applying machine learning to solve complex data challenges in the e-commerce and marketing space.
- You thrive in a fast-paced, startup environment and can manage multiple projects concurrently.
- You're results-driven and excited by the prospect of directly impacting revenue generation through innovative AI solutions.
- You're a self-starter with a desire to take ownership of the data engineering and machine learning practice within a growing company.
- You have a keen interest in the intersection of data engineering and machine learning, particularly in its applications in marketing technology.
Who you would work with You'll work directly with the founder, a serial entrepreneur with extensive experience in scaling startups and enterprise businesses.
You'll also collaborate closely with their Machine Learning team and an assistant professor and ML/marketing researcher at the University of Toronto.
Your first 3 months you will: Dive deep into our existing data and ML infrastructure, identifying areas for improvement and optimization.
Design and implement scalable data and machine learning architectures to support our AI-driven marketing solutions.
Develop connectors to extract data from multiple e-commerce and email marketing APIs, ensuring seamless integration with our ML models.
Work closely with our ML team to create integrated data pipelines that support efficient model training and deployment.
Establish best practices for data governance, documentation, security, and ML model management.
Participate in rapid experimentation and innovation, delivering results and learnings within the first month.