Machine Learning Engineer

• Work with colleagues from our Data & AI department and collaborate closely with product managers, engineers, and commercial stakeholders.
• Design, build, and operate machine learning systems for retail media use cases such as sponsored product ranking, audience segmentation, campaign optimization, attribution, and performance measurement.
• Translate business and product requirements into scalable ML solutions, balancing model quality, latency, reliability, scalability, and maintainability.
• Develop robust ML pipelines for feature engineering, training, evaluation, deployment, monitoring, and continuous model improvement.
• Bring models into production using our cloud-based stack and ensure they are reliable, observable, and maintainable over time.
• Communicate technical decisions, assumptions, limitations, and uncertainty clearly to product, engineering, and business stakeholders.
• Contribute to ML engineering standards, best practices, and knowledge sharing within the team.

Senior ML Engineer

• Support the development, training, and evaluation of ML/AI models using Python and industry-standard frameworks
• Apply supervised learning techniques such as Logistic Regression, Gradient Boosting Machines (GBM), and Random Forests to solve classification and regression problems
• Explore and implement Generative AI models (e.g., transformers, diffusion models) for use cases such as text generation, summarization, or synthetic data creation
• Analyze structured and unstructured datasets using pandas, NumPy, and matplotlib/seaborn for data wrangling and visualization
• Use scikit-learn, XGBoost, and TensorFlow/PyTorch to build and validate predictive models
• Contribute to software development projects using Python, Java, or Kotlin
• Present findings, model performance, and project outcomes to teams
• Participate in code reviews, team meetings, and brainstorming sessions to support collaborative innovation

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Senior ML Engineer

ML Engineer – Summer Intern, Paid