Software Engineer (SE / Sr SE), Applied ML & Data Mining
Santa Clara, CA
- Pay
USD 130,000–220,000/year — pay source
Salary 130,000 – 220,000 USD per year Employment type
Read the full posting- Work setup
- Unconfirmed
- Employment
Full-time — employment source
Employment type Full-time
Read the full posting
What you’ll work on
Full postingYou will work at the intersection of applied machine learning, information retrieval, large-scale data processing, and product engineering.
Ensure that your work is performed in accordance with the company’s Quality Management System (QMS) requirements and contribute to continuous improvement efforts
From the employer’s posting
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.
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:
What you’ll bring
All qualificationsCore 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
Preferred experience
- 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
Qualification wording
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
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
Education & alternatives
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
Tools in this posting
- JavaScript
- Python
- SQL
- TypeScript
- PyTorch
- React
- TensorFlow
Source — Tool mentions in context
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
- 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
- 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
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
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
Salary
130,000 – 220,000 USD per year
Employment type
Full-time
Your next step
- Have your CV and examples of relevant work ready.
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Source & posting history
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
Salary 130,000 – 220,000 USD per year Employment type
- Location & working pattern
Santa Clara, CA
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
- Status in our records
- Active
- First seen by us
- Aug 5, 2026
- Recorded sightings
- 21
- Last seen by us
- Oct 8, 2026
- Employer says posted
- Jul 31, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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