Senior ML Engineer

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  Design, build, and deploy scalable machine learning systems across personalization, search, recommendations, and retrieval use cases

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  Develop and evaluate models using robust experimentation frameworks and data-driven methodologies

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  Own components of end-to-end ML pipelines, including feature engineering, model training, validation, deployment, and monitoring

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  Write production-quality code and contribute to scalable, maintainable ML infrastructure

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  Analyze large datasets to extract insights and translate business problems into well-defined ML tasks

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  Partner closely with product, design, engineering, and analytics teams to deliver solutions with measurable business impact

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  Participate in code reviews, model reviews, and design discussions to uphold engineering excellence

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  Contribute to documentation, knowledge sharing, and mentoring junior engineers where appropriate
   

• Bachelor’s or master’s Degree in a relevant field such as Computer Science, Data Science, Statistics, or a related quantitative discipline

• 4+ years of industry experience building and deploying machine learning systems in production environments

• Strong hands-on experience across the end-to-end ML lifecycle (data preparation, modeling, evaluation, deployment, monitoring)

• Proficiency in Python and common ML frameworks (e.g., PyTorch, TensorFlow, Scikit-learn)

• Experience working with structured and/or unstructured large-scale datasets

• Solid understanding of software engineering best practices (version control, testing, CI/CD)

• Collaborative mindset and ability to work effectively in a global team
   

• MS or PhD in a relevant field

• Experience with personalization, recommendation systems, search, or ranking systems

• Experience with Generative AI, LLM fine-tuning, prompt engineering, or RAG systems

• Experience building or operating ML systems at scale (cloud platforms such as AWS, GCP, or Azure)

• Experience with model deployment frameworks or MLOps tools (e.g., MLflow, Kubeflow, SageMaker, Vertex AI)

• Familiarity with experimentation platforms (A/B testing, online metrics evaluation)

• Ability to communicate technical concepts clearly to cross-functional stakeholders
   

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