Senior Machine Learning Engineer

About the role

Build and deploy machine learning models that improve recommendations, ranking, and personalization, driving measurable impact on user experience and engagement. Own problems end‑to‑end, from data exploration and feature engineering through model training, evaluation, and production deployment.

Key responsibilities

• Build and deploy ML models that enhance recommendations, ranking, and personalization.
• Own problems end‑to‑end, from data exploration and feature engineering through model training, evaluation, and production deployment.
• Develop and maintain scalable ML pipelines using tools such as Spark and Airflow.
• Apply modern ML frameworks (e.g., PyTorch or TensorFlow) to design, train, and optimize models in production environments.
• Contribute to experimentation frameworks, including A/B testing and offline evaluation.
• Collaborate cross‑functionally with Product and Engineering to translate product questions into ML solutions.
• Take ownership of delivering high‑quality solutions from insight to impact, balancing speed and rigor.
• Apply responsible AI practices ensuring fairness, transparency, and safety.

Required profile

• Typically 5–8 years of experience, or equivalent demonstrated skills.
• Strong experience building and deploying machine learning models in production.
• Proficiency in Python and at least one major ML framework (PyTorch, TensorFlow).
• Experience with data pipelines and distributed systems such as Spark and Airflow.
• Familiarity with experimentation methodologies like A/B testing and model evaluation.
• Ability to collaborate effectively across functions with strong ownership.
• Demonstrates an agile mindset, adapting approaches based on data and evolving priorities.
• Growing AI fluency, able to independently apply ML techniques and emerging tools (including LLMs) responsibly.

Required skills

• Python
• PyTorch
• TensorFlow
• Apache Spark
• Apache Airflow
• Machine learning model development and deployment
• Data pipeline engineering
• Experimentation (A/B testing) methodologies