Staff AI Engineer, Model Post-Training and Alignment
OKX · On-site
MeritLog read this listing from OKX's Greenhouse job board and last checked it on September 10, 2026.
Source: the employer's Greenhouse job board. Open the original listing for current details.
Job details
- Work model
- On-site
- Salary
- Not listed by source
- Location
- APAC
Hiring context
How this role compares at OKX
OKX has 345 live roles in MeritLog’s catalog across 12 job families, and 97 of them are in engineering. 0 of those listings publish a pay range, a disclosure rate of 0%.
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What the role asks for
What you'd do
- Lead and execute the full post-training pipeline for large language models (LLMs), including supervised fine-tuning, preference optimization, and reinforcement learning–based methods.
- Design and implement advanced training paradigms such as DPO (Direct Preference Optimization) and GRPO (Generalized Reward Policy Optimization).
- Develop domain-specific data recipes, curation strategies, and augmentation pipelines to optimize task performance.
- Conduct post-training of specialized small models from scratch, including architecture selection, dataset construction, and optimization strategy.
- Build and refine Reward Models to support alignment and downstream optimization.
- Design and implement RLAIF (Reinforcement Learning from AI Feedback) closed-loop systems.
- Optimize inference efficiency and deploy models using low-latency serving frameworks such as vLLM and SGLang.
- Evaluate model performance using both automated benchmarks and human/AI feedback loops.
- Collaborate with research and infrastructure teams to productionize training and deployment workflows.
- Bachelor's in Computer Science, AI, Machine Learning, or related fields with at least 8 years of industry experience.
- Strong hands-on experience across the full post-training pipeline for large models.
- Deep familiarity with preference learning and alignment techniques, including DPO, GRPO, and RL-based post-training methodologies.
- Experience training and post-training specialized small models from scratch.
- Solid understanding of reinforcement learning fundamentals and their application to model alignment.
- Experience deploying models in low-latency production environments using frameworks such as vLLM, SGLang, or similar.
Parsed by MeritLog from the employer’s own posting. The full description follows below.
Job description
Who We Are At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom. OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves. Across our multiple offices globally, we are united by our core principles: We Before Me, Do the Right Thing, and Get Things Done. These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er. OKX is part of OKG, a group that brings the value of Blockchain to users around the world, through our leading products OKX, OKX Wallet, OKLink and more. About the Opportunity We are seeking a highly skilled and hands-on Machine Learning Engineer specializing in large model post-training and alignment. This role focuses on designing, executing, and optimizing post-training pipelines to improve model performance, controllability, domain adaptation, and reasoning capabilities. You will work across the full lifecycle of post-training-from data strategy and reward modeling to reinforcement learning–based optimization and production-grade inference deployment. What You’ll Be Doing • Lead and execute the full post-training pipeline for large language models (LLMs), including supervised fine-tuning, preference optimization, and reinforcement learning–based methods. • Design and implement advanced training paradigms such as DPO (Direct Preference Optimization) and GRPO (Generalized Reward Policy Optimization). • Develop domain-specific data recipes, curation strategies, and augmentation pipelines to optimize task performance. • Conduct post-training of specialized small models from scratch, including architecture selection, dataset construction, and optimization strategy. • Build and refine Reward Models to support alignment and downstream optimization. • Design and implement RLAIF (Reinforcement Learning from AI Feedback) closed-loop systems. • Optimize inference efficiency and deploy models using low-latency serving frameworks such as vLLM and SGLang. • Evaluate model performance using both automated benchmarks and human/AI feedback loops. • Collaborate with research and infrastructure teams to productionize training and deployment workflows. What We Look For In You • Bachelor's in Computer Science, AI, Machine Learning, or related fields with at least 8 years of industry experience. • Strong hands-on experience across the full post-training pipeline for large models. • Deep familiarity with preference learning and alignment techniques, including DPO, GRPO, and RL-based post-training methodologies. • Proven experience designing domain-specific data strategies and training methodologies. • Experience training and post-training specialized small models from scratch. • Solid understanding of reinforcement learning fundamentals and their application to model alignment. • Experience deploying models in low-latency production environments using frameworks such as vLLM, SGLang, or similar. Perks & Benefits • Competitive total compensation package • L&D programs and Education subsidy for employees' growth and development • Various team building programs and company events • Wellness and meal allowances • Comprehensive healthcare schemes for employees and dependants • More that we love to tell you along the process! Please note that Hong Kong is a group-level service hub, and OKX does not carry on a business of operating a virtual asset trading platform in Hong Kong. Notice: All official OKX vacancies are published on this website. While roles may appear on selected third-party platforms from time to time, information on other sites may be inaccurate or outdated. If in doubt, please apply directly through our official careers website. Information collected and processed as part of the recruitment process of any job application you choose to submit is subject to OKX's Candidate Privacy Notice.
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