1 day ago
Palo Alto, CA, USASenior
Base Salary
$115k - $230k/yr
Responsibilities
- Lead the architecture and implementation of machine learning models in collaboration with Product, Business Units, and Engineering teams.
- Design and develop scalable infrastructure for model training, automated hyperparameter tuning, and deployment pipelines.
- Write modular, maintainable, production-grade code for ML services and APIs.
- Debug and optimize model performance, reliability, speed, and efficiency in production.
- Own the complete ML model lifecycle, including monitoring, retraining, and model version management.
- Mentor junior machine learning engineers and lead technical decision-making and engineering best practices.
- Collaborate with data engineering, software development, and product management teams to integrate and operate models in production.
- Evaluate and integrate new machine learning techniques and systems engineering tools.
Requirements
- Bachelor of Science in Computer Science, Machine Learning, Engineering, or a related technical field.
- At least 6 years of hands-on production experience applying machine learning techniques including deep learning, reinforcement learning, and NLP.
- At least 6 years of experience with data warehouses, streaming platforms, relational and NoSQL databases, distributed processing, and workflow management components.
- At least 6 years of professional software development experience using at least two general-purpose programming languages such as Java, C++, Python, or C#.
- At least 6 years of experience with TensorFlow, PyTorch, or Scikit-learn for model development.
- At least 4 years of experience with AWS, Azure, or GCP, Docker, and Kubernetes.
- Proven experience deploying scalable, reliable, and highly available machine learning models in production.
- Extensive experience with object-oriented design, design patterns, clean code, version control, distributed systems, ML operations, system architecture, performance optimization, fault-tolerant systems, monitoring, and logging.
- Experience designing and deploying ML models in cloud environments and familiarity with AWS SageMaker, GCP AI Platform, or Azure Machine Learning.
- Preferred experience with high-performance distributed systems, large-scale data ingestion and processing, real-time inference, low-latency model serving, serverless or managed ML services, and GPU/TPU optimization.
- An advanced degree such as an M.Sc. or Ph.D. is preferred.
Benefits
- Personalized development programs, mentorship, and certification assistance.
- Inclusive and collaborative culture focused on shared success.
- Competitive benefits and flexibility to support employee well-being and future needs.
Tech Stack
Apache AirflowApache CassandraApache KafkaApache SparkAWSAzureC#C++DockerGitGoogle Cloud PlatformJavaKubernetesMongoDBPostgreSQLPythonPyTorchscikit-learnSnowflakeTensorFlow
Categories
About GEICO
GEICO sells auto and other personal lines insurance to U.S. consumers through a primarily direct-to-consumer model via web, mobile, and phone, with some local agents. Its products include car, motorcycle, RV, boat, homeowners, renters, condo, umbrella, and commercial auto coverage, plus roadside assistance. Founded in 1936 and headquartered in Bethesda, Maryland, GEICO is a subsidiary of Berkshire Hathaway and is among the largest auto insurers in the United States.