Machine Learning Engineer
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Join to apply for the Machine Learning Engineer role at Tennr

Join to apply for the Machine Learning Engineer role at Tennr

About Tennr:Today, when you go to your doctor and need to be referred to a specialist (e.g., for sleep apnea), your doctor sends a fax (yes, in 2024, 90% of provider-provider communication is a 1980s fax). These are often converted into 20+ page PDFs, with handwritten (doctor's handwriting!) notes, in thousands of different formats. The problem is so complex that a person has to read it, type it up, and manually enter your information. Tennr built RaeLM (7B—trained on 3M+ documents) to read these docs, talk to your doc to ensure nothing is missed, and text you to help schedule your appointment so you can get better, faster.

About Tennr:Today, when you go to your doctor and need to be referred to a specialist (e.g., for sleep apnea), your doctor sends a fax (yes, in 2024, 90% of provider-provider communication is a 1980s fax). These are often converted into 20+ page PDFs, with handwritten (doctor's handwriting!) notes, in thousands of different formats. The problem is so complex that a person has to read it, type it up, and manually enter your information. Tennr built RaeLM (7B—trained on 3M+ documents) to read these docs, talk to your doc to ensure nothing is missed, and text you to help schedule your appointment so you can get better, faster.Tennr is a NYC-based tech company that launched out of Y-Combinator and is backed by Lightspeed Venture Partners, Andreessen Horowitz, Foundation Capital, The New Normal Fund, and other top investors.Key ResponsibilitiesMachine Learning Engineers at Tennr are expected to wear a variety of hats. In the role, you will be expected to do the following:

• End-to-End Model Development: Architect, train, deploy, and monitor machine learning models, especially open-source LLMs and traditional computer vision models, to deliver tangible value to Tennr's customers.
• Data Processing & ML Ops: Build, optimize, and maintain data pipelines and machine learning infrastructure, enhancing our operational capability as data volume and complexity grow.
• System Integration: Design and implement backend workflows leveraging machine learning to automate critical processes within Tennr's platform.
• Custom Model Development: Fine-tune large language models, vision language models, and traditional computer vision models tailored specifically for medical document understanding and related tasks.
• Product Collaboration: Work closely with sales, customer success, and implementation teams to integrate customer feedback into actionable improvements and innovative solutions.
• Evaluation and Optimization: Develop robust evaluation frameworks to measure model performance and efficacy within complex, multi-model systems.

Qualifications

• 3+ years of professional experience in an applied machine learning engineering role, ideally post-BS/MS.
• Proven experience deploying and maintaining machine learning models in production environments, preferably within startups or rapidly evolving companies.
• Practical experience fine-tuning open-source LLMs and/or traditional computer vision models.
• Familiarity with robust ML Ops stacks, infrastructure management, and operational best practices for machine learning at scale.
• Comfort working within complex systems that integrate multiple machine learning components, with experience building evaluation frameworks to ensure system performance.
• Academic background in machine learning, mathematics, or related fields preferred.
• Up-to-date knowledge of recent advancements in large language models (LLMs) and enthusiasm for tracking rapid developments in the space.
• Prior startup experience or exposure to environments leveraging state-of-the-art ML models strongly preferred.

Seniority level

• Seniority levelMid-Senior level

Employment type

• Employment typeFull-time

Job function

• Job functionEngineering and Information Technology
• IndustriesSoftware Development

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