Senior Machine Learning Engineer: ML Recall

Accountabilities • Develop and optimize modern search retrieval systems using dense and sparse models, query understanding, and other machine learning techniques.

• Build solutions that balance retrieval quality and strict latency requirements, ensuring relevant products are returned within milliseconds.

• Develop end-to-end visual and multimodal search capabilities, including image search, visual recommendations, and "shop the look" experiences.

• Train, fine-tune, evaluate, deploy, and continuously improve deep learning models used across multiple products and teams.

• Experiment with new model architectures, retrieval approaches, and techniques, validating their effectiveness through A/B testing and live traffic experiments.

• Address complex measurement challenges in search recall by developing reliable ground truth and evaluation methodologies for products that may otherwise be missed entirely.

• Design models that generalize across 40+ languages and 20+ domains without relying on customer-specific rules or overrides.

• Take ownership of machine learning initiatives from problem framing and research through production rollout and ongoing optimization.

• Collaborate with other engineering and machine learning teams whose products build on the models and capabilities you develop.

Requirements:

• 4+ years of experience building and shipping production machine learning systems.

• Professional experience with search, information retrieval, recommendation systems, or closely related machine learning applications.

• Hands-on experience training, fine-tuning, and evaluating transformer-based models.

• Strong Python and PyTorch skills, with practical experience developing production-quality ML solutions.

• Familiarity with data orchestration and large-scale data processing tools such as Spark and Airflow.

• Demonstrated experience owning machine learning models end to end, from problem formulation and experimentation to deployment and production monitoring.

• Experience designing and running A/B tests and using experimental results to assess and improve model impact.

• Strong analytical and problem-solving abilities, particularly when working with complex retrieval and relevance challenges.

• Excellent English communication skills and the ability to collaborate effectively in a distributed, technical environment.

Benefits:

• Unlimited vacation time, with employees strongly encouraged to take at least 3 weeks of vacation each year.

• Fully remote working environment, giving you flexibility over where you live and work.

• Work-from-home stipend to help you create an effective home-office setup.

• Apple laptop provided for new employees.

• Annual training and professional development budget.

• Maternity and paternity leave for eligible employees.

• Opportunity to work with experienced technical colleagues and contribute to high-impact machine learning projects.

• Base salary of $80,000–$120,000 USD , depending on knowledge, skills, experience, and interview results.

• Stock options in addition to the base salary.

• Regular team offsites designed to support collaboration and connection.

How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether?

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