Senior Staff Machine Learning Engineer, AI Modeling ...

GEICO . For more information, please .Senior Staff Machine Learning Engineer, AI Modeling and Research page is loaded## Senior Staff Machine Learning Engineer, AI Modeling and Researchlocations: Palo Alto, CAtime type: Full timeposted on: Posted 2 Days Agotime left to apply: End Date: September 30, 2025 (17 days left to apply)job requisition id: R0060031**At GEICO, we offer a rewarding career where your ambitions are met with endless possibilities.****Every day we honor our iconic brand by offering quality coverage to millions of customers and being there when they need us most. We thrive through relentless innovation to exceed our customers’ expectations while making a real impact for our company through our shared purpose.****When you join our company, we want you to feel valued, supported and proud to work here. That’s why we offer The GEICO Pledge: Great Company, Great Culture, Great Rewards and Great Careers.**GEICO is seeking an experienced Staff or Sr. Staff Machine Learning Engineer to join the AI organization. This person will take on a critical leadership role in designing, implementing, and deploying cutting-edge machine learning models that solve real-world business challenges. You will collaborate with various business units to build scalable, high-performance ML systems with a strong emphasis on system design. In addition to technical contributions, you will mentor junior engineers, drive the full lifecycle of machine learning model development, and ensure that models are seamlessly integrated into production. This position requires expertise in both machine learning and software engineering to develop robust, production-grade solutions.Key Responsibilities:* Lead the Design & Implementation of ML Models: Lead the architecture and implementation of machine learning models, working closely with Product, Business Units, and Engineering teams.* Build Scalable Infrastructure: Design and develop scalable infrastructure for model training, automated hyperparameter tuning, and deployment pipelines, ensuring that systems are reliable and performant at scale.* Write Production-Grade Code for ML Services and APIs: Write high-quality, maintainable production-grade code that turns machine learning models into deployable services and APIs. Ensure that code is modular and reusable for future ML projects.* Optimize Model Performance and Resolve Issues: Debug and troubleshoot model performance issues, track key metrics, and continuously enhance model reliability, speed, and efficiency in production environments.* End-to-End Model Lifecycle Management: Own the complete lifecycle of ML models, including monitoring, retraining, and managing versions of models to ensure they continue to meet business needs over time.* Leadership and Mentorship: Guide and mentor junior machine learning engineers, promote best practices in software engineering, model development, and deployment. Lead technical decision-making processes and foster collaboration within the team.* Collaboration Across Teams: Collaborate with cross-functional teams (e.g., data engineering, software development, and product management) to integrate machine learning models and ensure smooth deployment and operations in production systems.* Stay Up to Date with Industry Trends: Continuously explore and integrate new machine learning techniques and system engineering tools, ensuring the team remains at the forefront of machine learning and systems architecture practices.Basic Qualifications:* B.Sc. in Computer Science, Machine Learning, Engineering, or a related technical field.* 6+ years of hands-on experience applying machine learning techniques, including deep learning, reinforcement learning, and NLP in production environments.* 6+ years of experience utilizing open-source/cloud-agnostic components such as data warehouse (e.g. snowflake), streaming platform (e.g. Kafka), relational database (e.g. PostgreSQL), NoSQL (e.g. MongoDB, Cassandra), distributed processing (e.g. Spark, Ray), workflow management (e.g. Airflow, Temporal), etc.* 6+ years of professional software development experience with at least two general-purpose programming languages such as Java, C++, Python or C#.* 6+ years of experience with machine learning frameworks such as TensorFlow, PyTorch, Scikit-learn for model development.* At least 4 years of experience with cloud platforms (AWS, Azure, GCP) and containerization technologies such as Docker, as well as orchestration tools like Kubernetes.* Proven experience in deploying machine learning models in a production environment, ensuring scalability, reliability, and high availability.Core Engineering Skills & Knowledge:* Extensive experience with object-oriented design (OOD), design patterns, writing clean, and maintainable code. Proficiency in version control (Git) and familiarity with Agile methodologies.* Solid understanding of distributed systems and the challenges associated with scaling machine learning models in production, such as managing distributed data processing and microservices architectures.* Expertise in implementing MLOPs practices, including setting up continuous integration (CI), continuous delivery (CD), automated testing, and deployment pipelines for ML models.* Strong understanding of system architecture, performance optimization, designing fault-tolerant systems that handle large-scale data and high-volume requests.* Experience designing and deploying machine learning models using cloud-based environments like AWS, Azure, or Google Cloud. Familiarity with cloud-native tools such as AWS Sage Maker, GCP AI Platform, or Azure Machine Learning.* Experience setting up monitoring and logging systems to track performance in production environments and ensuring efficient resource utilization.Preferred Qualifications:* Experience with designing and building high-performance distributed systems that handle large-scale data ingestion and processing for machine learning workloads.* Experience with real-time inference pipelines and low-latency model serving.* Familiar with serverless computing or managed services for ML model deployment.* Advanced degree (M.Sc., Ph.D.) in a related field is a plus.* Experience in working with GPU/TPU optimization for accelerated model training and inference.**Annual Salary**$150,000.00 - $300,000.00The above annual salary range is a general guideline. Multiple factors are taken into consideration to arrive at the final hourly rate/ annual salary to be offered to the selected candidate. Factors include, but are not limited to, the scope and responsibilities of the role, the selected candidate’s work experience, education and training, the work location as well as market and business considerations.GEICO will consider sponsoring a new qualified applicant for employment authorization for this position.**The GEICO Pledge:****Great Company:** At GEICO, we help our customers through life’s twists and turns. Our mission is to protect people when they need it most and we’re constantly evolving to stay ahead of their needs.We’re an iconic brand that thrives on innovation, exceeding our customers’ expectations and enabling our collective success. From day one, you’ll take on exciting challenges that help you grow and collaborate with dynamic teams who want to make a positive impact on people’s lives.**Great Careers:** We offer a career where you can learn, grow, and thrive through personalized development programs, created with your career – and your potential – in mind. You’ll have access to industry leading training, certification assistance, career mentorship and coaching with supportive leaders at all levels.**Great Culture:** We foster an inclusive culture of shared success, rooted in integrity, a bias for action and a winning mindset. Grounded by our core values, we have an an established culture of caring, inclusion, and belonging, that values #J-18808-Ljbffr

Created: 2025-09-18