Sr.
Full-Stack Engineer Engagement Type: Contract - USD Location: Remote - LATAM - (EST time) Advanced English skills is required
About the Role
We're seeking a Senior Full Stack Engineer ready to play a starring role in shaping the future of cinema experiences.
From digital ticketing and mobile engagement to in-theater innovation, your code will help set the stage for unforgettable nights at the movies.
If you love the idea of blending creativity, technology, and storytelling, you belong in this production.
You'll work across our full technology stack as needed.
We value engineers who are curious, adaptable, and willing to jump into backend services, web platforms, or infrastructure work when the team needs it.
What will you be doing
Design, develop, test, and deploy software solutions that enhance cinema operations and elevate guest experiences.
Collaborate across product, design, and operations teams to translate business goals into elegant, scalable solutions.
Take ownership of projects from storyboard to premiere, seeing your work through from concept to production release.
Continuously refine performance, scalability, and reliability to keep the show running flawlessly.
Stay ahead of tech trends and pitch innovative ideas that make every visit to Regal a blockbuster experience.
About you
5+ years of professional software engineering experience.
Strong proficiency with React, NodeJS and .
NET.
Solid understanding of cloud platforms, CI/CD practices, and modern software architecture.
A creative, problem‐solving mindset with a knack for working independently.
A passion for technology and storytelling—bonus points if you've built consumer‐facing or mobile apps before.
AgileEngine is a‐world performance, low error rates, robust scalability, optimal memory usage and ensure continuous monitoring and iterative refinements for sustained improvements.
A degree in Computer Science or related field.
Ideally PhD in NLP, Machine Learning, or a related field,



complemented by a solid track record in AI R&D; (with good publications in A* conferences).
Must have knowledge of Metal Shading Language (MSL).
You should be comfortable writing custom compute shaders from scratch.
Proven experience in low‐level kernel optimizations and inference optimization on mobile devices is essential.
Your contributions should have led to measurable improvements in inference latency, throughput, and memory footprint for domain‐specific applications, particularly on resource‐constrained devices and edge platforms.
A deep understanding of modern model serving architectures and inference optimization techniques is required.
This includes state‐of‐the‐art methods for achieving low‐latency, high‐throughput performance, and efficient memory management in diverse, resource‐constrained deployment scenarios.
Must have strong expertise in writing GPU kernels for mobile devices (i.e., smartphones) as well as a deep understanding of model serving frameworks and engines.
Practical experience in developing and deploying end‐to‐end inference pipelines, from optimizing models for efficient serving to integrating these solutions on resource‐constrained devices is required.
Demonstrated ability to apply empirical research to overcome challenges in model serving, such as latency optimization, computational bottlenecks, and memory constraints.
You should be proficient in designing robust evaluation frameworks and iterating on optimization strategies to continuously push the boundaries of inference performance and system efficiency.
Distributed Inference Systems: Designing and optimizing high‐performance inference engines using techniques like Tensor Parallelism, Pipeline Parallelism, and Expert Parallelism to handle massive models on GPU clusters.
Deep understanding of the math and structure behind Diffusion Models and Vision Transformers
Understanding of Pruning, Quantization, Flash attention, KV Cache, Speculative Decoding (Eagle) etc.
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