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.
Qualifications
- 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.
The target base salary for this position ranges from $190,800/year to $286,800/year [in Zone 1, in Zone 4 or encompassing all Zones]. The target base salary will vary based on the job's location.
Our geographic zones are as follows:
Zone 1 - San Francisco / New York City / Seattle
Zone 2 - Los Angeles / Washington DC / Austin / Boston / Sacramento / San Diego
Zone 3 - Atlanta / Portland / Chicago / Philadelphia / Denver / Miami / Dallas / Raleigh
Zone 4 - All other US cities
The base salary range listed for this full-time position excludes commission (if applicable), equity and benefits. The pay range shown on each job posting is the minimum and maximum target for new-hire salaries. Actual pay may be higher or lower depending on factors like skills, experience, and relevant education or training.
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