Software Engineer/Senior Software Engineer, Applied ML & Data Mining

PlusAI; Santa Clara (CA); On-site; USD 130,000 - 220,000; Full time

Job summary

PlusAI seeks a research-oriented data scientist/engineer to advance data mining, retrieval, and ranking for autonomous-driving datasets. You will identify valuable moments for training and evaluation and build tools for search, review, and curation used by autonomy and ML engineers.

Role spans applied ML, information retrieval, and large-scale data processing, contributing to vector search, multimodal representations, and scalable indexing pipelines.

Qualifications

• BS/MS/PhD in CS or ML or equivalent practical experience.
• Experience with ML/data-mining methods and frameworks (PyTorch, TensorFlow).
• Understanding of embeddings, similarity search, and dataset curation.
• Ability to own projects end-to-end with strong initiative.

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 retrieval and vector search.
• Build and operate distributed mining, inference, and indexing pipelines over fleet-scale imagery, video, time-series, and autonomy-system data.
• 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

Skills

PyTorch

TensorFlow

Data mining

ML research

Embeddings

Similarity search

Model evaluation

Education

CS/ML degree

Tools

Milvus

FAISS

pgvector

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.

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

Required Skills:

• BS, MS, or PhD in Computer Science, Machine Learning, or a related technical field, or equivalent practical experience
• Hands-on experience developing and evaluating machine-learning, data-mining, computer-vision, or information-retrieval methods with a framework such as PyTorch or TensorFlow, including experimentation, error analysis, and principled metrics
• Foundations for data-centric machine learning: an understanding of model uncertainty and evaluation, embeddings and similarity search, and how training-data composition shapes model behavior
• Self‑driven with a strong sense of ownership: a quick learner who is eager to take responsibility and drive projects forward end to end

Preferred Skills:

• Production full-stack experience spanning backend services and REST APIs, relational data modeling and SQL, and modern JavaScript or TypeScript frontend development using React or a comparable framework
• Experience improving models through data — training or fine-tuning, active learning and data flywheels, hard‑example mining, uncertainty or disagreement signals, dataset curation — ideally in autonomous driving, robotics, or perception
• Experience with embedding and multimodal models (CLIP‑style models, VLMs), vector databases (Milvus, FAISS, pgvector), or GPU batch inference at scale

$130,000 - $220,000 a year