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Sage

Senior Applied Machine Learning Engineer - Detect

Posted 3 Days Ago
Hybrid
New York, NY
180K-210K Annually
Senior level
Hybrid
New York, NY
180K-210K Annually
Senior level
The Senior Applied Machine Learning Engineer will manage AI models for fall detection, improve infrastructure, and enhance model accuracy in a collaborative environment focused on older adults' safety.
The summary above was generated by AI

Sage is on a mission to improve care and quality of life for older adults, starting with those residing in senior living facilities. Falls are the leading cause of injury-related death among adults over 65. And yet, fall prevention and emergency response systems for older adults are archaic and ineffective. At Sage we've built a more modern way of understanding when older adults need help, including methods for residents to alert caregivers when in need of help, and corresponding software for caregivers to triage response. Our company mission is to create a product that our client counterparts love, and this role is a key part of that objective.

Sage is a small, tight team of ambitious, multi-disciplinary entrepreneurs. We are a software-enabled, mission-driven company, and are focused only on the problems that are central to achieving that mission. At Sage, we work hard and fast but also know that to build a truly important company, we need to treat our work as a marathon, and not a sprint. The journey matters.

About this Role

As a Senior Applied Machine Learning Engineer on the Detect team, you'll own the end-to-end lifecycle of the AI models that power our camera-based detection system — from data collection and labeling through training, evaluation, and production deployment. Today, Detect uses frontier multi-modal vision models to analyze video streams and detect falls in real time. Your job is to make these models dramatically better and more capable.

You'll take ownership of our ML experimentation platform and infrastructure, maturing it into a robust system that enables the team to rapidly iterate on model quality at scale. You'll design repeatable fine-tuning pipelines that allow models to continuously improve with new production data, and expand the system's detection capabilities beyond falls into new behavioral categories. This is a hands-on, high-autonomy role where you'll directly impact the accuracy of a life-saving system used every day by caregivers across the country.

Responsibilities
  • Own and evolve our ML experimentation platform, maturing existing infrastructure into a production-grade system the team relies on daily
  • Build data pipelines for collecting, labeling, and preparing production video and image data for model training
  • Design repeatable fine-tuning and evaluation pipelines that enable rapid experimentation and measure model performance at scale
  • Improve detection accuracy and reduce false positives through prompt engineering, model fine-tuning, and novel inference strategies
  • Expand detection capabilities into new behavioral categories
  • Work closely with the backend engineering team to integrate model improvements into the real-time video processing pipeline
Minimum Qualifications
  • 5+ years of professional software engineering experience
  • Experience training, fine-tuning, or improving ML/AI models in a production setting
  • Strong understanding of model evaluation methodology and experiment tracking
  • Proficiency in Python or TypeScript
Preferred Qualifications
  • Experience with cloud AI platforms (Google Vertex AI, AWS SageMaker, or similar)
  • Experience fine-tuning multi-modal models (VLMs) or large language models (LLMs)
  • Familiarity with Kotlin, Java, or similar JVM languages
  • Background in computer vision, video processing, or working with image/video data at scale
  • Experience building internal ML tooling (labeling, experiment tracking, evaluation)
  • Experience maturing early-stage internal tools into production-grade systems
  • Full-stack capability with TypeScript/React for building internal tool UIs
Benefits and Pay

Our headquarters are located in New York City's Union Square. We believe in cross team collaboration. We think good ideas can come from anyone, and we've designed our processes to encourage participation from all. While we take our mission seriously, we don't take ourselves too seriously. We like to host offsites, outings, and team meals where we can connect as people, not just as colleagues. We offer office lunch and a fully stocked snack bar. While we are an in office culture, we allow up to 2 remote days per week.

Our benefits package for employees includes competitive base compensation along with stock options. The expected annual salary range for this role is $180,000 - $210,000 USD, depending upon the job level, which will depend on your level of expertise, your experience, and your qualifications. We also provide fully-paid health and dental insurance coverage for all of our employees, along with other health benefits including vision insurance, membership to premium primary and urgent care, and online medical health providers. We also have a take as you need time off policy, in addition to 7 paid holidays and a company wide winter break during the holidays.

EEO Statement

Sage is an equal opportunity employer that is committed to diversity and inclusion in the workplace. We prohibit discrimination and harassment of any kind based on race, color, sex, religion, sexual orientation, national origin, disability, genetic information, pregnancy, or any other protected characteristic as outlined by federal, state, or local laws.

This policy applies to all employment practices within our organization, including hiring, recruiting, promotion, termination, layoff, recall, leave of absence, compensation, benefits, training, and apprenticeship. Sage makes hiring decisions based solely on qualifications, merit, and business needs at the time.

Top Skills

Aws Sagemaker
Google Vertex Ai
Python
Typescript

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