[Remote] Senior MLOps Engineer at Twin Health

United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Healthcare, Digital Health, BiotechnologyIndustries

Requirements

Bachelor's or Master's degree in Computer Science, Engineering, or a related field with 5+ years of industry experience
Familiarity with architectural frameworks of large, distributed, and high-scale ML applications. Experience in the implementation of applications using LLMs and GenAI is a huge plus
Solid understanding of MLOps, data structures, and software design principles
Proficiency in programming with Python and experience in other languages like Java or Go
Strong knowledge in deploying scalable machine learning models, including experience with Docker, Kubernetes, and microservices architecture
Experience with database technologies (e.g., SQL, NoSQL)

Responsibilities

Architect, design, and build robust and efficient AI/ML systems for a production environment, focusing on backend distributed systems, microservices, and ensuring system accuracy
Lead cross-functional initiatives end-to-end (scoping, timelines, dependencies), driving alignment across Data, Infra and ML Engineering
Collaborate closely with AI/ML engineers to optimize workflows for model training, real-time inference, monitoring, and troubleshooting
Be a subject matter expert on ML infrastructure, providing guidance to both internal teams and external stakeholders
Ensure operational excellence and reliability of ML systems. Define and enforce SLAs around system performance, including latency, throughput, and resource utilization
Develop tools for effective model management, continuous monitoring, and enhancing the efficiency and effectiveness of the entire ML lifecycle
Actively engage in mentorship and knowledge sharing to promote a culture of continuous learning and improvement within the team

Skills

MLOps

Machine Learning

Digital Twin

CGM

Kubernetes

Docker

CI/CD

AWS

GCP

Twin Health

Monitors and treats chronic metabolic diseases

About Twin Health

Twin Health focuses on addressing chronic metabolic diseases by targeting their root cause: damaged metabolism. The company operates in the healthcare and wellness market, specifically for individuals suffering from conditions like diabetes and Metabolic Syndrome. Twin Health uses its Whole Body Digital Twin technology, which combines sensors, artificial intelligence, and medical science to create a virtual model of the human body. This technology allows for real-time monitoring and analysis of a person's metabolic functions, enabling the creation of personalized treatment plans. Unlike its competitors, Twin Health emphasizes reversing and preventing these diseases through a subscription-based model that provides continuous support and updates. The goal of Twin Health is to effectively manage and reduce the prevalence of chronic metabolic diseases, improving the health of millions globally.

Mountain View, CaliforniaHeadquarters

2018Year Founded

$227.1MTotal Funding

LATE_VCCompany Stage

AI & Machine Learning, HealthcareIndustries

501-1,000Employees

Benefits

Health Insurance

Dental Insurance

Vision Insurance

401(k) Retirement Plan

Unlimited Paid Time Off

Parental Leave

Health Savings Account/Flexible Spending Account

Company Equity

Remote Work Options

Flexible Work Hours

Risks

Competition from companies like Virta Health threatens Twin Health's market share.

Privacy concerns and regulatory scrutiny challenge wearable technology data collection.

Economic downturn may impact consumer spending on health subscriptions, affecting revenue growth.

Differentiation

Twin Health's Whole Body Digital Twin offers real-time metabolic monitoring and personalized treatment.

The platform integrates AI, sensors, and medical science to reverse chronic diseases.

Twin Health targets root causes of metabolic diseases, unlike competitors focusing on symptoms.

Upsides

Growing digital twin market offers strong potential for Twin Health's technology.

Increasing trend in personalized medicine aligns with Twin Health's treatment approach.

AI-driven solutions adoption by healthcare providers enhances collaboration opportunities for Twin Health.

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