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Senior Machine Learning Engineer at Nitra | Washington, DC

NitraWashington, District of Columbia, USA
On-site Full-time

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Experience Level

Senior

Qualifications

Key Responsibilities: Architect and build next-generation AI solutions. Design systems for internal workflows and customer-facing applications. Collaborate with cross-functional teams to integrate AI capabilities into products. Continuously optimize and refine machine learning models. Ideal Candidate: Proven experience in machine learning and platform engineering. Strong programming skills in Python or similar languages. Experience with AI frameworks and tools. Ability to work in a fast-paced, high-intensity environment.

About the job

Nitra develops technology that helps healthcare professionals run their practices more efficiently, allowing them to focus on patient care. The company’s AI-driven tools aim to simplify operations throughout the healthcare system.

Backed by leading investors and guided by experienced founders, Nitra is growing quickly and building for long-term impact. The team brings experience from companies like Microsoft, Meta, Plaid, PayPal, and BCG. A sense of urgency and ambition shapes the culture.

Role overview

The Senior Machine Learning Engineer will design and build Nitra’s data and AI platform. This work supports both healthcare and fintech solutions, touching internal workflows and customer-facing products.

This role blends applied AI with platform engineering. Projects include architecting and deploying systems that improve internal operations (such as go-to-market planning and product intelligence) and developing features for products like revenue cycle management, care coordination, and voice AI.

Location

This position is based in Washington, District of Columbia, USA.

About Nitra

Nitra is on a mission to transform the healthcare industry through cutting-edge technology. Our team is composed of experts from top tech companies, and we are supported by leading venture capital firms. Join us as we redefine healthcare efficiency and empower professionals to focus on what truly matters.

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