Software Engineer, ML Infrastructure
$90,000–$120,000 year
Remote · New York City, New York, United States or Edmonton, Alberta, Canada
Job Summary
As a Software Engineer for the Machine Learning Infrastructure team, you will design, build, and maintain a scalable data processing platform that supports data partnerships, ML research, and autonomy engineering. Responsibilities include developing data processing pipelines, implementing data discovery features, creating natural language querying systems, and maintaining orchestration systems. You will require a BS or MS in computer science, and have over 3 years' industry experience in large-volume data processing and ML feature extraction, alongside skills in Python, SQL, and familiarity with data annotation tools.
Required Qualifications
- BS or MS in computer science with focus in data engineering and/or machine learning
- 3+ years of industry experience building, running and improving large-volume data processing, feature extraction, data annotation workflows
- Experience building data mining and search capabilities
- Experience with both Python and SQL is required
- Solid understanding of data distributions and their impact on ML Models
- Hands-on experience and good understanding of LLMs, VLMs, embeddings, vector databases
- Experience with data annotation providers such as CVAT, LabelBox, LabelStudio, etc
Desired Qualifications
- Experience with integrating cloud inference platforms for LLMs/VLMS (ChatGPT, Gemini, etc)
- Experience working with Multi Modal data (Lidar, Camera, etc)
- Experience with robotics systems
- Experience optimizing large scale vector databases
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