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Sandbar is building human-computer interface products, starting with Stream, a private voice ring and conversational interface featured in major publications. The company was founded by engineers from Meta, CTRL-labs, Google, Apple, Fitbit, Peloton, and Equinox.
As a Machine Learning Engineer, you will develop software and ML algorithms for human-computer interface products. Key responsibilities include:
- Design system architectures involving large language models for conversational interfaces, information retrieval, and digital automation tasks
- Develop and deploy ML-based applications with focus on data curation and model training
- Research and develop applications using LLMs (OpenAI GPT, Anthropic Claude, Meta Llama)
- Conduct quantitative analysis using data science and statistical methods to optimize model performance
- Build real-time ML systems, including speech-to-text for voice conversation, vision-language models for image processing, and other real-time ML applications
- Implement retrieval augmented generation (RAG) systems to improve information retrieval accuracy
- Optimize systems for latency, reliability, and cost
- Work with cloud platforms (AWS/GCP) and deployment tools (Docker, TorchServe, Lambda, SageMaker)
Required qualifications:
- Bachelor's degree in computer science, engineering, data science, or machine learning
- 2+ years as a machine learning engineer
- 2+ years building and deploying ML applications with data curation and model training
- 2+ years developing LLM-based applications (GPT, Claude, Llama)
- 2+ years quantitative analysis and data science
- 2+ years Python programming
- 2+ years building real-time ML systems in professional context
- 1+ year AWS or GCP experience
- 1+ year Docker, TorchServe, Lambda, or SageMaker
- 1+ year developing RAG systems in production
- Prior startup experience (founding through Series A)
The role is hybrid with 3 days/week in-office requirement in NYC. Benefits include health/vision/dental, 401(k), unlimited PTO, and early-stage equity.
