Machine Learning Engineer

We're looking for versatile engineers who thrive at the intersection of product and infrastructure, eager to solve tough challenges in real-time AI, and excited to redefine how enterprises use intelligent agents. You will play a key role in building the product interfaces and backend systems that bring our AI agents to life. You will work across the stack, from scalable APIs and data pipelines to intuitive front-end dashboards, ensuring seamless integration between cutting-edge AI models and enterprise users. This role is ideal for engineers who thrive at the intersection of product and infrastructure and want to support Nurix's journey to redefine how enterprises use AI.

The core responsibilities for the job include the following:

Backend Development:

• Design and implement robust, scalable APIs (Python, Node.js ) that power AI/LLM services.
• Build data ingestion and orchestration layers that connect ML models with enterprise workflows.
• Ensure high performance, security, and reliability in real-time environments.

Integration and Support:

• Work closely with AI/ML engineers to integrate conversational AI models into production systems.
• Collaborate with the principal architect to ensure end-to-end system efficiency, low latency, and scalability.
• Support product teams in delivering enterprise-ready features.

Collaboration and Culture:

• Contribute to code reviews, design discussions, and best practices across the engineering team.
• Thrive in a fast-paced, high-growth startup environment with close alignment to research and infra leaders.

Requirements:

• 4+ years of experience.
• Strong proficiency in Python or Node.js .
• Experience with modern web frameworks (React, Next.js, or similar).
• Knowledge of databases (SQL/NoSQL), REST APIs, and microservices architectures.
• Familiarity with containerization and cloud platforms (AWS, GCP, or Azure).
• Strong problem-solving skills and ability to deliver production-quality code.
• Experience building platforms that integrate with AI/ML or data-intensive backends.
• Familiarity with real-time systems, WebSockets, or event-driven architectures.
• Exposure to MLOps or ML integration workflows.