LendingClub · 7 hours ago
Sr ML Ops Engineer
San Francisco, CA
Full-time
Hybrid
Senior Level
$176K/yr - $205K/yr
6+ years expLendingClub is the leading digital marketplace bank in the U.S., dedicated to helping members secure financial goals. They are seeking a Sr ML Ops Engineer to build and scale the ML platform and infrastructure, enabling efficient deployment and monitoring of machine learning models across various business functions.
Consumer LendingCreditFinanceFinancial ServicesFinTechLendingPeer to PeerPersonal Finance
Hiring Manager
Kat Greco
Responsibilities
Design, build, and maintain scalable machine learning infrastructure - including feature stores, model registries, and deployment pipelines - to enable efficient model experimentation and productionization
Implement end-to-end MLOps practices for automated continuous training, testing, deployment, versioning of workflows, and monitoring of ML models using modern frameworks (e.g., MLflow, SageMaker, Databricks, Kubeflow)
Build and maintain scalable ML pipelines for data ingestion, feature engineering, training, and deployment, ensuring reliability, observability, and compliance with LendingClub’s data security policies
Collaborate closely with data scientists to transition prototypes into robust, production-grade solutions - ensuring reproducibility, performance optimization, and version control
Build standards, tools and libraries to streamline model lifecycle operations (training, evaluation, deployment) for other teams across LendingClub
Create and maintain monitoring systems for model performance, data drift, and feature quality - with automated alerting and retraining triggers
Ensure compliance and governance of ML assets through audit logging, explainability tooling (SHAP, LIME, feature attribution), and model documentation practices that align with regulatory standards (e.g., Fair Lending, FCRA)
Integrate ML systems with business applications, APIs, and microservices to deliver real-time intelligence to customer-facing and internal decisioning systems
Collaborate with platform, DevOps, and security teams to establish standardized infrastructure, CI/CD pipelines, and deployment environments for ML workloads
Drive adoption of Responsible AI principles - ensuring fairness, interpretability, and transparency in models used for credit, risk, and customer decisions
Automate evidence packaging for internal audits and regulatory reviews, including data lineage, test results, and approval history
Conduct performance benchmarking and cost optimization for ML workloads across cloud and compute resources
Qualification
Required
6+ years of experience in Machine Learning Engineering, Data Engineering, or MLOps
Bachelor'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
Preferred
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
Benefits
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
Company
LendingClub
Since our founding in 2007, we have transformed the banking industry by bringing a traditional credit product - the installment loan - online and we’ve been on the fast track ever since.
1001-5000 employees
H1B Sponsorship
LendingClub has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2023 (3)
2022 (26)
2021 (19)
2020 (106)
Funding
Current Stage
Public CompanyTotal Funding
$392.23MKey Investors
Kleiner PerkinsUnion Square VenturesFoundation Capital
2017-04-09Post Ipo Equity
2014-12-11IPO
2014-08-22Series Unknown
Leadership Team
Scott Sanborn
Chief Executive Officer
Drew LaBenne
Chief Financial Officer
Recent News
p2p-banking.com
2025-12-24
2025-11-24
Company data provided by crunchbase