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Data & AnalyticsHybrid

Software Engineer (SE / Sr SE), Applied ML & Data Mining

PlusAI · Hybrid

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Last seen by MeritLog September 9, 2026Source: LeverSource version: lever-postings-v1

MeritLog read this listing from PlusAI's Lever job board and last checked it on September 9, 2026.

Source: the employer's Lever job board. Open the original listing for current details.

Job details

Work model
Hybrid
Salary
$130,000 - $220,000
Location
Santa Clara, CA
Occupation
Software Developers(O*NET 15-1252.00)

Hiring context

How this role compares at PlusAI

PlusAI has 39 live roles in MeritLog’s catalog across 5 job families, and 11 of them are in data & analytics. 33 of those listings publish a pay range, a disclosure rate of 85%.

This role's posted range of $130,000 - $220,000 sits above 63% of the 32 other PlusAI roles quoted over the same currency and period.

Counted across the job boards MeritLog tracks, at the time this page was served. Pay comparisons use only listings that publish a complete range in the same currency and period.

Job description

Finding the right data is central to improving autonomous-driving models. Among petabytes of fleet data, you will develop methods that identify and rank the most valuable moments for training and evaluation, then turn those methods into reliable tools that autonomy and ML engineers use to search, review, and curate datasets. You will work at the intersection of applied machine learning, information retrieval, large-scale data processing, and product engineering. We welcome candidates with ML or data-mining foundations who are excited to grow across scalable systems and the product stack. We are open to candidates at either the Software Engineer or Senior Software Engineer level. Level will be determined by experience, technical depth, scope of ownership, and demonstrated impact. You do not need experience with every technology in our stack; we value strong fundamentals, ownership, and the ability to learn. Responsibilities: Develop and evaluate mining, retrieval, and ranking methods using signals such as model confidence, disagreement, embeddings, anomalies, temporal behavior, and learned representations Build and evolve semantic image/video/scenario search, including text-to-image/video and image-to-image or video-to-video retrieval, vector search, metadata and temporal or spatial filters, task-specific ranking, and search quality, freshness, latency, and reliability Build and operate distributed mining, inference, and indexing pipelines over fleet-scale imagery, video, time-series, and autonomy-system data, including GPU batch inference, embedding generation, reproducible candidate datasets, and reliable index refreshes Design and ship mining products end to end: Python APIs and services, relational data models, asynchronous jobs, modern TypeScript/React search and review experiences, deployment, access control, testing, observability, and production reliability Ensure that your work is performed in accordance with the company’s Quality Management System (QMS) requirements and contribute to continuous improvement efforts

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