Machine Learning Engineer

📋 Job Overview

Sandbar is an interface company in New York City. We aim to augment individuals so we can each think, act, and move more freely. Our team has built SW, ML, and HW products across Meta, CTRL-labs, Google, Apple, Fitbit, Peloton, and Equinox. Our first product, Stream, is a self extension—a private voice ring and conversational interface. Stream has been featured in WSJ, Bloomberg, & Wired, and begins shipping in Summer '26. Join us in creating technology that extends human thinking.

🏢 About Sandbar

Sandbar is an interface company in New York City. We aim to augment individuals so we can each think, act, and move more freely. Our team has built SW, ML, and HW products across Meta, CTRL-labs, Google, Apple, Fitbit, Peloton, and Equinox. Our first product, Stream, is a self extension—a private voice ring and conversational interface. Stream has been featured in WSJ, Bloomberg, & Wired, and begins shipping in Summer '26.

🎯 The Role

This role involves developing software and machine learning algorithms for use in human computer interface products. This includes designing system architectures involving large language models for conversational, information retrieval, and digital automation tasks. This also includes utilizing data science and statistical methods to analyze and optimize machine learning model performance across tasks. Lastly, this includes optimizing the aforementioned systems for latency, reliability, and cost. Telecommuting permitted. 3x/week in office required.

✅ Key Responsibilities

• Develop software and machine learning algorithms for human computer interface products
• Design system architectures involving large language models for conversational, information retrieval, and digital automation tasks
• Utilize data science and statistical methods to analyze and optimize machine learning model performance
• Optimize systems for latency, reliability, and cost

📌 Required Qualifications

• Bachelor’s degree in computer science, engineering, data science or machine learning plus 2 years of experience as a machine learning engineer
• 2 years building & deploying ML-based applications, including data curation and model training
• 2 years of experience researching and developing applications based on large language models
• 2 years of experience in quantitative analysis based on data science
• 2 years of experience in Python programming language
• 2 years of experience building real-time applications utilizing ML models
• 1 year of experience with AWS or GCP
• 1 year of experience with Docker, TorchServe, AWS Lambda, or SageMaker
• 1 year of experience developing retrieval augmented generation systems
• Experience in at least 1 startup-stage company
• Must be able to successfully complete competency-based interviews

🎁 Benefits

• Health, vision, and dental benefits
• Company-sponsored 401(k)
• Unlimited PTO and sick time
• Early stage equity