Machine Learning Engineer

Location: Ho Chi Minh City, Ho Chi Minh City, Vietnam
Posted: 5d ago

pythonrustllm

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About this role

<div class="content-intro">OPSWAT, a global leader in IT, OT, and ICS critical infrastructure cybersecurity, delivers an end-to-end platform that gives public and private sector organizations and enterprises the critical advantage needed to protect their complex networks, secure their devices, and ensure compliance. Over the last 20 years our commitment to innovative technology has earned the trust of more than 1,700 organizations, governments, and institutions globally, solidifying our role in protecting the world’s critical infrastructure and securing our way of life.</div>The Position MetaDefender Core is OPSWAT's file security platform, trusted where the stakes are highest: nuclear plants, defense networks, and the banks that move the world's money. The most sensitive of those customers cannot send a single byte to anyone's cloud, so the AI must run entirely on their hardware, inside the product.  This role is for the engineer who would rather own a model than call someone else: you build the training data, the fine-tuning, the evaluation, and you make the call on what ships. Every AI assistant you have ever used lives in a data center; yours will run on the customer's own hardware, inside some of the most protected networks in the world.  What You Will be Doing  <ul> <li>Own the model track end to end: training data, fine-tuning runs, evaluation, and release, with scope and ownership growing by level. </li> <li>Build and maintain the evaluation gate for every model to change and make it something the team trusts more than its own intuition. </li> <li>Build the data pipelines that produce training datasets, enforcing grounding so the model can only state what it has actually read. </li> <li>Shape how the agent behaves: its instructions, its tool contracts, and how it recovers when the model gets something wrong. </li> <li>Own the model's security posture: harden it against prompt injection and misuse, make sure it never exposes internal information, and never lets itself be steered into guiding users toward unsafe actions. </li> <li>Serve models on constrained customer hardware: quantization, inference runtimes, and the memory / latency / quality trade-off. </li> <li>Ship into a production Rust service, collaborating closely with the engineering team, Product Management, and QA. </li> </ul> What We Need from You  <ul> <li>Bachelor's degree in a technical field or equivalent practical experience. </li> <li>Experience fine-tuning open-weight LLMs using LoRA, QLoRA, or similar techniques.</li> <li>Strong Python, including building data pipelines for training datasets. </li> <li>Experience keeping model output grounded: retrieval-backed generation, hallucination control, and output traceable to a source the model reads. </li> <li>Experience with LLM serving and inference (e.g. vLLM, Ollama), including quantization and the memory / latency / quality trade-off on constrained hardware. </li> <li>Familiarity with tool-calling / agent-based LLM applications. </li> <li>Ability to design and run model evaluations for non-deterministic systems: you can name a metric you designed and the number you moved. </li> <li>Working knowledge of SQL. </li> <li>Strong verbal and written communication skills in English: the language of the team, the docs, and th

Machine Learning Engineer

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