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# Software Engineer III, GenAI Data Operations Research

- **Company:** Hackajob Ltd
- **Location:** Leeds, UK
- **Salary:** £100,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Big Data, Software Debugging, Distributed Computing Environment, Design of User Interfaces, Python (Programming Language), DataOps, Software Engineering, Reinforcement Learning, Data Processing, Graphics Processing Unit (GPU), Deep Learning, Model Validation, Generative AI, Information Technology, Hardware Acceleration, Machine Learning Operations, Programming Languages, Data Generation
- **Published:** September 3, 2026
- **Apply:** https://www.adzuna.co.uk/jobs/details/5868805832

## About the Role

* Bachelors degree or equivalent practical experience.
 * 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
 * 1 year of experience with one or more of the following: speech/audio, reinforcement learning, ML infrastructure, or specialization in another ML field.
 * 1 year of experience with ML infrastructure, such as model deployment, model evaluation, data processing, or debugging.
 * Masters degree or PhD in Computer Science or a related technical field.
 * Experience architecting infrastructure for bulk inference and metadata extraction.
 * Exposure to or direct experience with human-centric generative pipelines.
 * Proficiency in Python and experience with frameworks for large-scale data processing.
 * Ability to enable end-to-end fine-tuning for foundational GenAI models and optimize them for production environments, including specialized hardware like TPUs.

## Description

* Build scalable infrastructure and modular toolkits for at-scale distributed data processing, GenAI data generation, and metadata extraction.
 * Run, monitor, and scale deep learning experiments across compute clusters, and develop efficient inference pipelines using JAX.
 * Lead high-volume synthetic datasets, including metadata deliveries for XR and device projects.
 * Integrate automated evaluation and filtering tools to measure domain gaps and ensure high-quality, photorealistic data.
 * Migrate pipelines to specialized hardware accelerators like TPUs or GPUs for efficient production-scale inference.

Technologies:

 * AI
 * Android
 * Architect
 * Fine-tuning
 * Hardware
 * Mobile
 * Python
 * Web
 * XR
 * Security
 * UX UI Design


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