Senior ML Engineer serving as an individual contributor in generative AI at GEICO. Collaborating with teams to design, develop, and deploy AI systems that drive business value.
About the role
- Senior Software Engineer designing and operating ML infrastructure for Plaid's AI initiatives. Collaborating with product teams to accelerate AI-powered financial experiences and ensure scalable ML systems.
Responsibilities
- Design and implement large-scale ML infrastructure, including feature stores, pipelines, deployment tooling, and inference systems.
- Drive the rollout of Plaid’s next-generation feature store to improve reliability and velocity of model development.
- Help define and evangelize an ML Ops “golden path” for secure, scalable model training, deployment, and monitoring.
- Ensure operational excellence of ML pipelines and services, including reliability, scalability, performance, and cost efficiency.
- Collaborate with ML product teams to understand requirements and deliver solutions that accelerate experimentation and iteration.
- Contribute to technical strategy and architecture discussions within the team.
- Mentor and support other engineers through code reviews, design discussions, and technical guidance.
Requirements
- 5+ years of industry experience as a software engineer, with strong focus on ML/AI infrastructure or large-scale distributed systems.
- Hands-on expertise in building and operating ML platforms (e.g., feature stores, data pipelines, training/inference frameworks).
- Proven experience delivering reliable and scalable infrastructure in production.
- Solid understanding of ML Ops concepts and tooling, as well as best practices for observability, security, and reliability.
- Strong communication skills and ability to collaborate across teams.
- [Nice to have] Experience with ML Ops tools such as MLFlow, SageMaker, or model registries.
- [Nice to have] Exposure to modern AI infrastructure environments (LLMs, real-time inference, agentic models).
- [Nice to have] Background in scaling ML infrastructure in fast-paced product environments.
Benefits
- Health insurance
- Retirement plans
- Paid time off
- Flexible work arrangements
- Professional development
Job title
Job type
Experience level
Salary
Degree requirement
Tech skills
Location requirements
Senior Staff Machine Learning Engineer at GEICO, enhancing service productivity through AI technologies. Collaborating with dynamic teams to develop and deploy scalable AI workflows across Geico.
Staff AI Engineer at GEICO designing and deploying AI platforms for virtual agent workflows. Collaborating with teams to improve service for millions of customers.
Machine Learning Engineer at Tilt, developing personalisation solutions across various app surfaces. Collaborate with teams to enhance recommendation systems on a video - first shopping platform.
Senior Machine Learning Engineer architecting next - generation AI platforms for healthcare and fintech with Nitra's diverse team. Focused on data pipelines, ML infrastructure, and production - ready AI systems.
Senior Machine Learning Engineer architecting and building Nitra's data and AI platform. Driving intelligent products across healthcare and fintech industries with applied AI and platform engineering.
Machine Learning Engineer developing and implementing ML models for lending at Blue Whale Lending LLC. Collaborating with teams to enhance data insights and validate model performance.
Applied ML Engineer contributing to machine learning and perception tasks for edge - intelligent maritime systems. Collaborating with cross - functional teams to deliver real - world AI solutions.
AI/ML Engineer building data science and AI solutions for Pharma and MedTech clients on Azure. Collaborating with teams to deliver end - to - end machine learning projects.
ML Engineering Lead at Saris AI tackling multi - modal AI systems in banking. Drive technical direction and build high - performing teams in an early - stage startup environment.