below marketmost similar roles pay hereabove market
This role pays more than
94%
of similar roles. Most pay
$202,800–$254,750
— the blue band above.
At the midpoint, this role pays about
$309k
versus about
$229k
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
70 open roles
on FindRole.
Listed pay typically runs
$190,800–$262,800
across 70 roles with salary data.
The Staff Machine Learning Engineer (Research Scientist) - DFAI joins the Data Foundation & AI team to build shared machine learning infrastructure and foundational models. You will lead the technical strategy for foundation models built on financial datasets, overseeing the full machine learning lifecycle from data curation and pretraining objectives to production serving, monitoring, and observability. You will design model architectures, establish rigorous evaluation frameworks, and build scalable pipelines that translate research into production impact. The role requires deep expertise in Transformers, LLMs, and distributed training using Python and software engineering fundamentals. You will solve the problem of transforming unique financial network data into scalable, general-purpose representations, enabling reusable ML infrastructure and reducing duplicated modeling efforts across various downstream product applications and teams.
What does a Machine Learning Engineer earn in New York?
Median $246150 from 57 postings across 20 companies.
Own the end-to-end technical strategy for foundation models from pretraining architecture to production serving.
Drive research decisions from initial experimentation through to production systems that serve 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.
Partner with cross-functional teams to define how products integrate with and adapt foundation models.
Mentor engineers across experience levels and 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 (serving infra, feature stores) (preferred).