Note: The job is a remote job and is open to candidates in USA. KinderCare Learning Companies is the first and only early childhood education provider recognized with the Gallup Exceptional Workplace Award, offering a variety of early education and child care options. As a Senior Machine Learning Engineer, you will apply your expertise in the Databricks Lakehouse Platform to develop and operationalize scalable predictive modeling applications, while leading end-to-end ML workflows and collaborating with cross-functional teams.
Responsibilities
- Databricks-Native ML Development: Design, develop, and deploy machine learning solutions using Databricks technologies including PySpark, Spark SQL, MLflow, Feature Store, AutoML, and notebooks to standardize experimentation and feature reuse
- End-to-End ML Pipeline Architecture: Build scalable ML pipelines across the full lifecycle—from data ingestion and feature engineering to model validation, deployment, monitoring, and retraining within the Lakehouse platform
- MLOps & Model Lifecycle Management: Implement CI/CD, model versioning, governance, automated retraining, and production deployment using MLflow Model Registry, Databricks Workflows, and Model Serving
- Advanced Databricks Capabilities: Leverage AutoML, Mosaic AI components, vector search, and Model Serving to accelerate experimentation and enterprise AI adoption while maintaining governance and scalability
- Applied Data Science & Mentorship: Perform exploratory analysis and apply statistical and machine learning techniques including regression, classification, and clustering. Mentor junior developers and analytics professionals on ML guidelines and operationalization
- Cross-Functional Collaboration: Partner with Data Engineering, Analytics, Product, and business collaborators to align AI solutions with enterprise architecture, governance, and business objectives
- Performance, Governance & Reliability: Optimize Spark performance and cost efficiency while implementing monitoring, alerting, lineage tracking, and access controls through Unity Catalog and related governance frameworks
- Platform Enablement & Scalability: Develop reusable frameworks, templates, and standards that accelerate scalable, governed ML adoption across the organization
Skills
- Bachelor's degree in Computer Science, Engineering, Data Science, Mathematics, Statistics, or a related quantitative field (or equivalent experience)
- 4+ years of experience in Machine Learning Engineering or Data Engineering, with significant hands-on expertise in Databricks technologies including Delta Lake, MLflow, Feature Store, and Unity Catalog
- Success in delivering production-grade ML pipelines end-to-end, from data ingestion and feature engineering through deployment, monitoring, and continuous improvement
- Experience using AI-assisted development tools such as Cursor, Claude, or GitHub Copilot to accelerate development, testing, and optimization of distributed ML workloads
- Strong proficiency in Python, PySpark, and Spark SQL, with deep knowledge of distributed computing, Spark optimization, and scalable ML architecture
- Experience designing Databricks-native ML solutions employing platform capabilities such as MLflow, AutoML, Feature Store, Delta Lake, and Model Serving
- Familiarity with CI/CD and DevOps tooling including GitHub Actions, Azure DevOps, or GitLab CI
- Hands-on experience building and evaluating ML models using frameworks such as scikit-learn, XGBoost, or LightGBM
- Solid grasp of feature engineering, experiment tracking, model validation, and performance evaluation
- Ability to mentor engineers and data scientists, lead technical discussions, and influence ML engineering methodologies across teams
- Experience building reusable ML frameworks and modernizing legacy workflows into scalable, governed Databricks-native pipelines
- Master's degree or higher in a related field preferred
- Experience with RAG architectures, vector databases, embedding pipelines, and LLM-based applications is a plus
Benefits
- Discounted child care benefits
- Medical, dental, and vision benefits for your family (and pets, too!)
- Employee assistance programs
- Health and wellness programs
- Paid time off
- Discounts for work necessities, such as cell phones
Company Overview