below marketmost similar roles pay hereabove market
This role pays more than
95%
of similar roles. Most pay
$211,200–$254,750
— the blue band above.
At the midpoint, this role pays about
$309k
versus about
$233k
for comparable roles.
Based on 240 similar postings.
Employer
About Plaid
Plaid is a financial technology company that builds a data network powering digital finance applications, enabling consumers to securely connect their financial accounts to apps and services. Industry: Financial Technology & Data Infrastructure
Plaid currently has
73 open roles
on FindRole.
Listed pay typically runs
$190,800–$262,800
across 73 roles with salary data.
The Staff Machine Learning Engineer (Research Scientist) - DFAI joins the Data Foundation & AI team to build shared machine learning and AI infrastructure. This role involves leading the technical strategy for foundation models, overseeing the full machine learning lifecycle from large-scale data curation and pretraining to production serving, evaluation, and monitoring. You will design model architectures, define pretraining objectives, and build scalable pipelines that transform financial network data into general-purpose representations. Key requirements include deep expertise in Transformers, LLMs, and foundation models, along with proficiency in Python, distributed training, and software engineering fundamentals. You will solve complex problems by creating reusable ML infrastructure and establishing rigorous evaluation frameworks to power diverse downstream product applications across the organization's financial data ecosystem.
What does a Machine Learning Engineer earn in California?
Median $235750 from 200 postings across 34 companies.
Own the end-to-end technical strategy for foundation models from pretraining architecture to production serving.
Drive research initiatives that transition from experimentation to production systems serving real customers.
Manage the full ML stack including pretraining objectives, architecture design, distributed training, and monitoring.
Establish rigorous evaluation frameworks to measure model performance across diverse use cases.
Build scalable, repeatable pipelines that translate machine learning research into production impact.
Define integration patterns and standards for how products adapt and utilize foundation models.
Mentor engineers across experience levels to elevate engineering and experimentation standards.
Communicate technical advancements internally and externally as a representative of Plaid’s AI capabilities.
What we're looking for
MS candidates must have 7–12+ years of industry experience with a track record of technical leadership and production delivery.
PhD candidates must have 5–9+ years of industry experience with evidence of technical leadership and end-to-end production ownership.
Prior technical leadership experience as a tech lead, principal, or staff engineer with demonstrated cross-team influence and mentorship is required.
Deep expertise in Transformers, LLMs, and Foundation Models, including large-scale training or domain adaptation, is required.
Proven track record of end-to-end production ownership, shipping models through training, serving, monitoring, and iteration in live environments is required.
Distributed training experience and strong Python and software engineering fundamentals at a staff level are required.
Fintech or financial data domain experience (preferred).
External publications, open-source contributions, or experience defining ML platform capabilities are preferred.