Senior Machine Learning Engineer

You hold a Master’s or Ph.D. in a quantitative field, such as Computer Science, Statistics, Mathematics, or a related discipline.

You possess 4+ years of experience in data science and machine learning, ideally within the tech industry and marketplace environments.

You have hands-on experience post-training and self-hosting open-weight LLMs (e.g., fine-tuning, quantization, serving infrastructure such as vLLM, SGLang ) rather than relying solely on third-party APIs.

You have a deep understanding of evaluation metrics across deep learning and classical ML and can design evaluation strategies that catch regressions before they reach production.

You have end-to-end fluency in the MLOps lifecycle — data versioning, feature stores, CI/CD for ML, model monitoring/observability, and retraining pipelines — not just model development.

You are knowledgeable about large-scale distributed application architecture, design, implementation, and performance tuning.

You have the ability to drive the roadmap and direction of scalable, production-quality systems end-to-end, and effectively communicate cross-functionally with Product and Engineering teams.

You have practical knowledge of advanced machine learning algorithms and deep learning to deploy for search systems, information retrieval, and ranking algorithms.

You are proficient in SQL, Python and ML frameworks (such as TensorFlow and PyTorch) with strong coding skills.

You possess excellent communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.

We know that the best ideas come from teams where diverse points of view uncover new solutions to hard problems. We welcome and value individuals who bring diverse life experiences, educational backgrounds, cultures, and work experiences.

Our hiring process may utilize artificial intelligence (AI) tools to assist in candidate screening and assessment. Our AI tools are designed to complement, not replace, human decision-making.