Senior Machine Learning Engineer: Search Quality

About the role

This role focuses on advancing the search and discovery platform for e-commerce. A key responsibility involves developing and fine-tuning large language models (LLMs) to evaluate search relevance and understand user intent. The engineer will also work on aligning these models with actual user behavior to enhance the accuracy of search results.

The position demands expertise in maintaining high-quality search performance in a production environment. This includes optimizing real-time processes like reranking, filtering, and signal computation, all while adhering to strict latency requirements. Success in this area means ensuring the search platform delivers fast and accurate results consistently.

Another core aspect of the job is establishing automated systems for monitoring search quality. This involves creating pipelines that can detect performance degradations and generate actionable recommendations for improvements. The goal is to proactively identify and address issues, ensuring the platform remains robust and effective for global e-commerce brands.

The base salary for this role ranges from $115,000 to $195,500 USD, with stock options offered in addition.

Skills that matter here

• Python: This role requires strong Python skills for developing and deploying machine learning systems, especially with LLMs.
• PyTorch: Fluency in PyTorch is essential for fine-tuning models and working with LLM deployments.
• SQL: Proficiency in SQL is needed for data handling and analysis within the machine learning pipelines.
• Spark: Experience with Spark is required for data orchestration and processing large datasets in ML workflows.
• Airflow: Familiarity with Airflow is necessary for managing and automating data and ML pipelines.

Who this role suits

• A candidate with at least four years of experience shipping production machine learning systems.
• Someone who has worked with search, information retrieval, or recommendation systems previously.
• An individual skilled in fine-tuning, evaluation frameworks, and scaling LLM deployments.
• A person comfortable collaborating with cross-functional teams including ranking, product, and data engineering.

From the employer

• LLM-based evaluation: fine-tune models to assess relevance, understand query intent, and align judgments with user behavior.
• Real-time quality in production: reranking, filtering, and signal computation with strict latency requirements.
• Automated quality monitoring: pipelines to detect degradations and generate actionable recommendations.

• 4+ years shipping production ML systems
• Experience with search, information retrieval, or recommendation systems
• Hands-on experience with fine-tuning, evaluation frameworks, and scaling LLM deployments
• Strong Python and PyTorch; fluency in SQL and data orchestration tools (Spark, Airflow)
• Experience designing and running A/B tests to validate model impact
• Excellent English communication skills
• Experience collaborating in cross-functional teams (ranking, product, data engineering)

• Work with smart and empathetic people who will help you grow and make a meaningful impact.
• Regular team offsite events to connect and collaborate.
• Fully remote team - choose where you live.
• Unlimited vacation time - we strongly encourage all of our employees take at least 3 weeks per year.
• Work from home stipend for home office setup.
• Apple laptops provided for new employees.
• Training and development budget refreshed each year.
• Maternity & Paternity leave for qualified employees.
• Base salary: $80k–$120K USD, depending on knowledge, skills, experience, and interview results.
• Stock options offered in addition to the base salary.