Sr Machine Learning Platform EngineerLendingClub • San Francisco, CA, United States
Sr Machine Learning Platform Engineer
LendingClub • San Francisco, CA, United States
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job_description.job_card.job_descriptionBachelor's degree or higher in a related field; or equivalent work experience Strong foundation in ML engineering, with experience building and scaling pipelines and platforms in production Proficient in Python and experienced with data transformation and orchestration tools such as dbt (for modeling), Dagster (for orchestration), and Databricks (for large-scale data and model workflows) Deep understanding of the end-to-end ML lifecycle, from data ingestion and feature engineering to model deployment and monitoring Hands-on experience or interest in data quality and observability frameworks, such as Elementary, and you appreciate how data reliability underpins model performance Experience implementing or supporting MLOps practices using frameworks like MLflow, SageMaker, or similar tools within Databricks or AWS Comfortable working in a cloud-native environment (AWS preferred) and using infrastructure-as-code (Terraform, CloudFormation) to automate deployments Strong collaboration skills and the ability to partner with data engineers, data scientists, and product teams to make ML accessible, reliable, and compliant across domains You thrive in a FinTech environment, balancing innovation with rigor around governance, explainability, and model monitoring.6+ years of experience in Machine Learning Engineering, Data Engineering, or MLOps Experience with LLM integration (RAG pipelines, vector databases) Exposure to risk modeling, credit scoring, or fraud detection systems Familiarity with FinTech data privacy laws and model documentation standards Contributions to open-source ML infrastructure or platform components Work Location San Francisco The above locations are eligible offices for this role. The locations have been determined to foster in-person collaboration with this role’s team or the related business lines. We utilize a hybrid work model, and our teams are in-office Tuesdays, Wednesdays, and Thursdays. In-person attendance is essential for this role’s success, and remote placement will not be considered. LendingClub offers relocation, based on actual job level. Time Zone Requirements Primarily PT While the position will primarily work local hours, LendingClub is headquartered in Pacific Time and our ideal candidate will be flexible working across time zones when necessary. Travel Requirements As needed travel to LendingClub offices and / or other locations, as needed. Compensation The target base salary range for this position is 176,000-205,000. The base salary of the role will be determined by job-related knowledge, experience, education, skills, and location. Base salary is just one part of LendingClub’s Total Rewards package. You may also be eligible for long-term awards (equity) and an annual bonus (which is based on company performance, employee performance and eligible earnings). We’re creating new financial services solutions for our members based on fairness, simplicity, and heart, and we treat our employees the same way. We offer a competitive benefits package that includes medical, dental and vision plans for employees and their families, 401(k) match, health and wellness programs, flexible time off policies for salaried employees, up to 16 weeks paid parental leave and more. #LI-Hybrid #LI-JH1
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Machine Learning Engineer • San Francisco, CA, United States
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