Remote opportunity at
Stack AVSenior Software Engineer, ML Platform
Stack AV builds advanced autonomous systems and artificial intelligence technology tailored to the trucking transportation sector, focusing on operational safety and reliability. The ML Data Understanding…
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About This Role
Stack AV builds advanced autonomous systems and artificial intelligence technology tailored to the trucking transportation sector, focusing on operational safety and reliability. The ML Data Understanding team provides comprehensive data support spanning mining, training, and safety evaluation to power machine learning applications. As a Senior Software Engineer, ML Platform, you will architect next-generation multimodal semantic search and data discovery platforms for autonomous driving development. You will work with frontier large…
Job Description
Stack AV builds advanced autonomous systems and artificial intelligence technology tailored to the trucking transportation sector, focusing on operational safety and reliability. The ML Data Understanding team provides comprehensive data support spanning mining, training, and safety evaluation to power machine learning applications.
As a Senior Software Engineer, ML Platform, you will architect next-generation multimodal semantic search and data discovery platforms for autonomous driving development. You will work with frontier large language models, visual language models, Retrieval Augmented Generation techniques, and vector databases to establish agentic data mining and curation workflows.
This remote position involves building real-time semantic search services for text, images, and video, developing high-throughput stream and batch processing pipelines using technologies such as Ray, Spark, and LanceDB, and delivering both onboard C++ and offboard machine learning infrastructure solutions.
Responsibilities
- Architect multimodal semantic search and data discovery platforms using AI-assisted software engineering
- Apply frontier large language models, visual language models, and Retrieval Augmented Generation techniques
- Construct agentic data mining, semantic search, and data curation workflows for a recursive self-improvement machine learning loop
- Develop platform infrastructure for vector databases and real-time querying alongside batch and stream processing using tools like Ray, Spark, and LanceDB
- Deliver end-to-end data mining solutions spanning onboard C++ and offboard infrastructure
- Build real-time semantic search services for text, images, and videos alongside vector databases
- Identify and resolve performance issues within existing machine learning infrastructure
- Design low-latency and high-throughput stream or batch processing pipelines
- Lead technical discussions across multiple organizations to deliver timely solutions
- Write high-performance and readable Python and C++ code
Requirements
- Bring at least five years of relevant domain experience
- Demonstrate experience with both machine learning platforms and building machine learning-based applications
- Show a proven track record of constructing scalable and reliable infrastructure in fast-paced environments
- Possess a deep understanding of design trade-offs with the ability to articulate them and align with others
- Have a hands-on background developing semantic search infrastructure, generating multimodal embeddings, and managing vector databases
- Demonstrate experience with model training infrastructure, model optimization, large data processing pipelines, or multi-modal data indexing
Qualifications
- Experience building machine learning models or infrastructure within autonomous vehicles, perception, or decision-making domains
Core Skills
Frequently Asked Questions
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Is this position remote?
Yes, the source posting specifies that this role is remote.
What is the employment type?
The position is full-time.
What salary does this role offer?
The posting does not specify a salary.
What technical background is required for this role?
Applicants must have at least five years of relevant domain experience, a background in machine learning platforms and applications, hands-on experience with semantic search and vector databases, and proficiency in Python or C++.
Sample Interview Questions
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