This role sits at the core of a next-generation ecommerce search and discovery platform that operates at massive global scale. You will be responsible for building and optimizing machine learning systems that directly impact relevance, recall, and business-critical outcomes such as conversion and revenue. Working on transformer-based and multimodal models, you will help shape how users discover products across search, recommendations, and visual shopping experiences. The environment is highly technical and innovation-driven, with a strong emphasis on production-grade ML systems and measurable impact. You will collaborate with engineers across distributed teams to push the boundaries of LLMs, deep learning, and large-scale data systems. This is an opportunity to work on one of the most advanced AI-driven ecommerce search infrastructures in the industry.

Accountabilities

Design, build, and deploy robust machine learning systems for search and discovery, including NLP, image-based, and multimodal models that improve recall and relevance.
Develop and optimize ML/DL models using transformer architectures and LLM techniques to enhance system performance and business KPIs.
Translate research ideas and hypotheses into production-ready engineering solutions that improve search quality, ranking, and user experience.
Work on large-scale distributed data pipelines and ML workflows using big data technologies to support end-to-end model development and deployment.
Collaborate closely with cross-functional engineering teams to integrate models into broader platforms and ensure system scalability and reliability.
Conduct performance optimization and iterative experimentation to continuously improve model efficiency and business impact.

Requirements

3+ years of professional experience in applied machine learning with a proven track record of delivering production-grade ML systems.
Strong expertise in NLP, particularly transformer-based models, along with solid understanding of classical machine learning techniques.
Advanced Python skills and hands-on experience with deep learning frameworks (PyTorch preferred).
Strong experience with SQL (e.g., SparkSQL, MySQL or similar) and working knowledge of large-scale data processing systems such as PySpark.
Ability to translate business problems into data-driven hypotheses and implement scalable engineering solutions with measurable impact.
Strong problem-solving mindset, proactivity, and ownership-oriented approach to technical challenges.
Excellent collaboration and communication skills, with the ability to explain complex ML concepts clearly and work effectively in team environments.
Nice to have: experience with A/B testing, cloud platforms (AWS/GCP/Azure), Rust or C/C++, strong algorithmic thinking, and interest in performance optimization.

Benefits

Fully remote work setup, allowing you to choose your location.
Unlimited vacation policy with encouragement to take at least 3 weeks off annually.
Home office stipend to support your remote work environment.
Company-provided Apple laptop for all new employees.
Annual learning and development budget for continuous professional growth.
Paid maternity and paternity leave for eligible employees.
Stock options in addition to a competitive base salary.
Regular team offsites to foster collaboration and connection.
Opportunity to work with highly skilled peers on impactful, large-scale AI systems.
Base salary range: $80,000 - $120,000 USD depending on experience and performance.

Senior Machine Learning Engineer: ML Recall

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