Machine Learning Engineer, Allurion
Comprehensive weight loss technology company
Job no longer available
Comprehensive weight loss technology company
101-200 employees
Job no longer available
101-200 employees
Company mission
Allurion's mission is to end obesity.
Role
Who you are
- Degree in a computational discipline (Computer Science, Electrical Engineering, Information Systems, Physics, Computational Biology, etc.)
- Strong interpersonal and communication skills
- Deep knowledge of machine learning, generative AI, and chatbots
- Strong understanding of statistics and information theory
- 2+ years of work experience (with a PhD) or 4+ years of work experience (with a bachelor's or master's) building and deploying ML models in production
- 5+ years of experience in computer programming, including proficiency in both interpreted (Python, R) and compiled (C++, Java) languages
- Familiarity with SQL or similar languages
- Strong data manipulation, data pipelines, and system administration skills
- Experience designing and implementing APIs and services
- Self-motivated, problem-solver, and able to thrive in a fast-paced environment with a positive attitude
- Rigorous, detail-oriented, efficient at multitasking, and strong organizational skills with a commitment to impeccable execution. You prioritize simple solutions and are obsessed with quality
What the job involves
- In addition to building machine learning models, you will craft production-level back-end APIs and systems
- As a leader in our organization, you will initiate and drive new projects, propelling your career while making a significant societal impact
- Develop and refine machine learning algorithms that drive innovation in our virtual care suite, automating patient care and enhancing our patient care platform
- Design, implement, and manage production-level backend APIs and systems, making your ML approaches accessible to our software engineering team
- Utilize ML and AI technologies to reduce bias in provider decision-making and present comprehensive, reliable data
- Lead ML projects from conception to deployment, collaborating with various teams
- Evaluate and optimize the performance of existing ML models
- Collaborate with the data team on collecting, preparing, and enriching data for ML models
- Keep abreast of the latest trends and advancements in ML, AI, and healthcare technology
Our take
Obesity is a growing problem worldwide, tripling over the past few decades with more than a billion people worldwide now classified as obese. Although the health effects can be deadly, many of the proposed solutions such as diet and exercise do not seem to have been effective. Enter Allurion, a company which seeks to end obesity through a "360-degree" approach.
While in current times weight loss is no longer driven by outdated aesthetic considerations, it's still true that diet and exercise alone do not always seem to work and the available alternatives require invasive surgery or endoscopy. This creates a space in the market which Allurion occupies with its combination of non-surgical gastric balloon to physically regulate hunger, app-based health tracker, and personalized nutrition and exercise plan. In over a decade it has treated over 100,000 patients in 60 countries.
Allurion has secured large amounts of investment, pushing its expansion into India and Brazil, and allowing it to hire highly qualified individuals to its board to speed its applications for approval in new markets as well as develop the product. This was followed by an IPO in 2023, boosting its efforts to research AI-based weight loss solutions.
Freddie
Company Specialist at Welcome to the Jungle
Insights
19% employee growth in 12 months
Company
Funding (last 2 of 8 rounds)
Apr 2021
$25m
EARLY VC
Jan 2020
$34m
EARLY VC
Total funding: $115.5m
Company benefits
- Aim & Enthusiasm
- Work-Life Integration
- Inclusive Benefits
- Advancement
Company HQ
Natick, MA
Leadership
Dr. Shantanu Gaur
(Co-Founder & CEO)Prior to becoming the CEO was the Chief Scientific Officer with Allurion. Obtained a medical degree from Harvard Medical School.
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