Senior/Lead Machine Learning Engineer

Role overview A senior technical position focused on building, deploying, and scaling machine learning solutions that improve product performance, monetization, and user experience. The role blends data science with hands-on engineering, covering the full ML lifecycle from data pipelines through model training to production integration. The selected engineer will collaborate across product, data, and engineering teams while exploring emerging areas such as large language models and generative AI.

Responsibilities - Design, train, evaluate, and deploy machine learning models that target product quality and revenue outcomes - Build and maintain data pipelines for extraction, transformation, and large-scale analysis - Apply statistical and ML techniques to surface patterns, insights, and optimization opportunities in real-world business problems - Integrate ML models into production systems and establish ongoing monitoring for reliability and performance - Prototype solutions using LLMs and generative AI tools, experimenting with emerging techniques to enhance existing workflows - Translate findings and recommendations into clear narratives for both technical peers and non-technical stakeholders

Requirements - Three or more years of hands-on experience in ML engineering or data science roles - Five or more years of total experience in software or data engineering - Strong proficiency in Python for model development and production code - Solid SQL skills for data querying, transformation, and analysis - Demonstrated ability to ship ML models end-to-end, from data preparation through deployment - Practical experience with LLM and generative AI tooling (e.g., OpenAI APIs, AI-assisted coding platforms) - Upper-intermediate English proficiency, B2 or higher

Nice to have - Familiarity with Databricks or comparable data platforms - Exposure to AWS or other cloud-based environments for ML workloads - Comfort working in .NET-based systems for integration points

Benefits and work setup - Remote-friendly work arrangement - Inclusive hiring practices with equal opportunity commitment across protected categories - Note: AI-assisted tools may be used to record, transcribe, and analyze interview responses