Staff Machine Learning Engineer

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.

Staff Machine Learning Engineer  

Overview: As a Staff Machine Learning Engineer, you will be the overall tech lead of a single AI/Machine Learning team, responsible for the tech design and tech health of the team. You will build and architect scalable and reliable AIML solutions that align with the company's tech paved path and stakeholder requirements. This role requires a minimum of 6 years of relevant experience. 

Key Responsibilities: 

System development: Architect scalable and reliable AIML solutions that align with the company's tech paved path and stakeholder requirements.  

Establish ML Best Practice: Develop and implement Software Development Lifecycle (SDLC) best practices for machine learning projects, ensuring scalable, secure, and reliable systems from model development to production deployment. Expected to stay hands-on coding about 70% of the time. 

Product Leadership & Feature Backlogs: Define the product roadmap for machine learning solutions and establish feature backlogs. Prioritize key ML features in collaboration with product managers, aligning them with business objectives and technical feasibility. 

Optimize Model Performance and Reliability 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, finetuning and managing versions of models to ensure they continue to meet business needs over time. 

Leadership and Mentorship: Guide and mentor machine learning engineers, promote best practices in software engineering, model development, and deployment. Lead technical decision-making processes and foster collaboration within the team. 

Minimal Qualifications: 

• Bachelor’s degree in Machine Learning, Computer Science, Statistics, Mathematics, or a related field; an advanced degree (master’s or Ph.D.) is highly desirable 

• At least 6 years of hands-on experience in machine learning and software engineering. 

• Technical Skills: 

• Deep proficiency in programming languages such as Python, Java, or similar, with a strong emphasis on coding excellence. 

• Proficiency in AIML frameworks such as TensorFlow, PyTorch, Scikit-learn, Langchain, langraph, etc. 

• Experience with SQL, Spark, and scripting languages such as Python for data processing and model development. 

• Expertise in cloud platforms (AWS, Azure, GCP) and containerization technologies such as Docker, as well as orchestration tools like Kubernetes. 

• Proven experience in deploying machine learning systems in a production environment, ensuring scalability, reliability, and high availability. 

• Core Engineering Skills: <