Software Engineer, ML Engineering

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Nex

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2017

🎮 Gaming

🥽 AR/VR

🛍️ eCommerce

💰 Series B on 2021-04

Gaming • AR/VR • eCommerce

Nex is a company that creates immersive motion games and experiences focused on physical play. They believe that physical activity is crucial for fun and social interaction, which is why they develop innovative games that transform everyday environments into engaging play spaces. With advanced motion technology, Nex enables sensor-free motion tracking on various devices, allowing users to enjoy games that make movement enjoyable and accessible.

📋 Description

• Design and build training pipelines, data workflows, and model integration systems • Develop infrastructure that accelerates research iteration and reduces turnaround time • Build systems for data collection, curation, and preprocessing at scale • Create tools and automation that move experiments toward production readiness • Optimize data pipelines for reliability, performance, and observability • Collaborate with ML researchers to understand their needs and remove technical blockers • Work on model serving infrastructure and integration with the production framework • Write clean, well-tested code that maintains high engineering standards • Participate in code reviews and help raise the engineering bar across the team • Contribute to shared tools, infrastructure, and cross-role projects (20% Time) • Work with the dual-leadership model (Engineering Manager and Tech Lead) to understand priorities and technical direction • Document systems and decisions to support team knowledge sharing

🎯 Requirements

• 3+ years of professional software engineering experience in building production ML systems, training infrastructure, or research platforms. • Proficiency in Python, additional experience with at least one other systems language (C++, C#, Java, Rust, or Go). • Hands-on experience with PyTorch or TensorFlow in production or research environments. • Experience building or maintaining ML training pipelines or data workflows. • Familiarity with model deployment, inference optimization, or MLOps practices.

🏖️ Benefits

• Competitive compensation package. • Flexible working hours and vacation policy. • Product-driven culture that treasures talents and individual growth. • Front-row seat and hands-on experience with cutting edge technologies in the evolving gaming field