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

PlusAI, Inc.; Santa Clara (CA); Hybrid; USD 140,000 - 210,000; Full time

Job summary

PlusAI, Inc. is seeking a Software Engineer (SE) or Senior SE to advance applied ML and data mining for autonomous driving.

You will design mining, retrieval, and ranking methods, and develop scalable tools for searching, reviewing, and curating petabytes of fleet data. The role covers Python APIs and services, vector search, embeddings, GPU batch inference, and end-to-end product delivery with modern TypeScript/React interfaces.

Qualifications

• BS/MS/PhD in CS/ML or related or equivalent practical experience.
• Hands-on experience with ML/data-mining/CV/IR frameworks (PyTorch/TF).
• Understanding data-centric ML: embeddings, similarity search, data composition impacts.
• Self-driven with ownership and ability to drive projects end-to-end.

Responsibilities

• Develop mining, retrieval, and ranking methods.
• Build semantic image/video/scenario search and vector search.
• Operate distributed mining, inference, and indexing pipelines at scale.
• Design and ship mining products end-to-end: Python APIs, services, and web interfaces.

Skills

ML foundations

Data mining

Computer vision

Information retrieval

Ownership mindset

Education

BS/MS/PhD in CS/ML or related

Tools

PyTorch

TensorFlow

Milvus

FAISS

pgvector

Job description

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

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.

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

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