Senior Machine Learning Engineer: ML Recall
New
J
JobgetherE-commerce search
Based in SwitzerlandFull-TimeSenior
SalaryBase salary of $80,000–$120,000 USD, depending on knowledge, skills, experience, and interview results. Stock options in addition to the base salary.
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Job Details
- Languages
- Excellent English communication skills
- Experience
- 4+ years of experience building and shipping production machine learning systems.
- Required Skills
- PythonMachine LearningPyTorchAirflowSparkA/B testing
Requirements
- Have 4+ years of experience building and shipping production machine learning systems.
- Bring professional experience in search, information retrieval, recommendation systems, or closely related machine learning applications.
- Have hands-on experience training, fine-tuning, and evaluating transformer-based models.
- Have strong Python and PyTorch skills and practical experience developing production-quality ML solutions.
- Be familiar with data orchestration and large-scale data processing tools such as Spark and Airflow.
- Have experience owning machine learning models end to end, from problem formulation and experimentation to deployment and production monitoring.
- Have experience designing and running A/B tests and using experimental results to assess and improve model impact.
- Bring strong analytical and problem-solving abilities, particularly for complex retrieval and relevance challenges.
- Have excellent English communication skills and be able to collaborate effectively in a distributed technical environment.
Responsibilities
- Develop and optimize search retrieval systems using dense and sparse models, query understanding, and machine learning techniques.
- Build retrieval solutions that balance relevance quality with millisecond-level latency requirements.
- Develop 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 across products and teams.
- Experiment with model architectures and retrieval approaches, validating results through A/B tests and live traffic experiments.
- Develop ground truth and evaluation methodologies for measuring search recall.
- Design models that generalize across 40+ languages and 20+ domains without customer-specific rules or overrides.
- Own machine learning initiatives from problem framing and research through production rollout and ongoing optimization.
- Collaborate with engineering and machine learning teams whose products use the models and capabilities developed.
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