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:
Extensive experience with object-oriented design (OOD), design patterns, and writing clean, maintainable code.
Solid understanding of distributed systems and the challenges associated with scaling machine learning models in production.
Expertise in implementing MLOps practices, including setting up continuous integration (CI), continuous delivery (CD), automated testing, and deployment pipelines for machine learning models.
Strong understanding of system architecture, performance optimization, and the ability to design fault-tolerant systems that handle large-scale data and high-volume requests.
Experience designing, building, and maintaining ETL pipelines, streamlining data collection, transformation, and storage for model development.
Proficient in containerizing applications using Docker and managing deployment and scaling using Kubernetes or similar orchestrators.
Experience setting up monitoring and logging systems for tracking model performance in production environments and ensuring efficient resource utilization.
Preferred Qualifications:
3 years interfacing directly with internal business stakeholders and/or external stakeholders on AIML initiatives
Working experience with cloud provider solutions such as Azure and AWS
Experience utilizing both open source (e.g. llama, Qwen, Mistral) and proprietary (e.g. GPT, Claude) LLMs for appropriate tasks
Experience with tools that power LLM-based AI agents: eval frameworks, agent tooling, RAG pipelines, prompt engineering, etc.
Experience building LLM-based AI agent workflows via both no code/low code and traditional high-code development environments
Experience in ideating, integrating, and designing applications and frontends using React or similar.
If you are passionate about pushing the boundaries of machine learning technology, thrive in a hands-on technical leadership role, and enjoy solving complex, large-scale problems, we encourage you to apply.
Annual Salary
$130,000.00 - $260,000.00The 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.
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 different perspectives. Our teams are led by dynamic, multi-faceted teams led by supportive leaders, driven by performance excellence and unified under a shared purpose.
As part of our culture, we also offer employee engagement and recognition programs that reward the positive impact our work makes on the lives of our customers.
Great Rewards: We offer compensation and benefits built to enhance your physical well-being, mental and emotional health and financial future.
The equal employment opportunity policy of the GEICO Companies provides for a fair and equal employment opportunity for all associates and job applicants regardless of race, color, religious creed, national origin, ancestry, age, gender, pregnancy, sexual orientation, gender identity, marital status, familial status, disability or genetic information, in compliance with applicable federal, state and local law. GEICO hires and promotes individuals solely on the basis of their qualifications for the job to be filled.
GEICO reasonably accommodates qualified individuals with disabilities to enable them to receive equal employment opportunity and/or perform the essential functions of the job, unless the accommodation would impose an undue hardship to the Company. This applies to all applicants and associates. GEICO also provides a work environment in which each associate is able to be productive and work to the best of their ability. We do not condone or tolerate an atmosphere of intimidation or harassment. We expect and require the cooperation of all associates in maintaining an atmosphere free from discrimination and harassment with mutual respect by and for all associates and applicants.