OpenNet

Develops mobile sports entertainment apps

Applied AI Engineer

Applied Machine LearningConfirmed live in the last 24 hours

Full-timeTaiwanNo salary listed

About the Job

Requirements

At least 3 years of experience in software engineering, machine learning engineering, or applied AI.
Experience delivering an LLM application or service used by real users, with clear evidence of personal contribution and results.
Strong Python skills and experience building APIs, processing data, and debugging software.
Hands-on experience in at least one area: LLM application development, model serving, model evaluation and fine-tuning, or coding-agent development.
Ability to design repeatable evaluations, investigate failures, and explain trade-offs among quality, response time, and cost.
Ability to discuss technical designs and document results in English when collaborating with international teams.
Experience operating open-weight models with frameworks such as vLLM or SGLang, including load testing and GPU memory optimisation.
Experience fine-tuning models with domain-specific data and validating improvements on test data kept separate from training.
Experience building document-grounded retrieval systems or coding agents integrated with repositories and automated tests.

Responsibilities

Build internal AI services using open-weight language models for document processing, customer support, and employee chat, replacing external APIs while preserving required functionality.
Connect models to company systems and approved data through APIs; implement output validation, access controls, failure handling, and fallback to approved providers.
Work with Infrastructure and DevOps teams to deploy models on company-controlled infrastructure and improve response times, concurrent request capacity, and serving costs using representative workloads.
Compare internal models with existing providers through repeatable quality, latency, and cost evaluations; use results to guide model selection, prompts, retrieval, and fine-tuning, and verify quality during staged rollouts.
Integrate internal models with coding assistants and agents that retrieve code, propose changes, and run tests within approved permissions; help teams adopt these tools through practical examples and training while preserving code-review and release requirements.
Track usage by business and service; compare actual operating costs with estimated external-provider costs for the same workload, and measure workflow time saved after review and rework alongside defect rates.

About OpenNet

OpenNet is a fast-growing technology company with products reaching 20+ countries worldwide.

We bring together talented people who enjoy solving challenges, moving fast, and learning from one another. We value collaboration, flexibility, growth, and work-life balance — creating an environment where people can do great work and enjoy the journey along the way.

What you'll be doing

We are hiring engineers with complementary strengths. Projects will be assigned based on each engineer’s experience.
1. Build internal AI services using open-weight language models for document processing, customer support and employee chat, replacing external APIs while preserving required functionality.
2. Connect models to company systems and approved data through APIs. Implement output validation, access controls, failure handling and fallback to approved providers.
3. Work with Infrastructure and DevOps teams to deploy models on company-controlled infrastructure. Improve response times, concurrent request capacity and serving costs using representative workloads.
4. Compare internal models with existing providers through repeatable quality, latency and cost evaluations. Use the results to guide model selection, prompts, retrieval and fine-tuning, and verify quality during staged rollouts.
5. Integrate internal models with coding assistants and agents that retrieve code, propose changes and run tests within approved permissions. Help teams adopt these tools through practical examples and training, preserving code-review and release requirements.
6. Track usage by business and service. Compare actual operating costs with estimated external-provider costs for the same workload, and measure workflow time saved after review and rework, alongside defect rates.

Requirements

3+ years of experience in software engineering, machine learning engineering or applied AI.
Experience delivering an LLM application or service used by real users, with clear evidence of your contribution and results.
Strong Python skills and experience building APIs, processing data and debugging software.
Hands-on experience in at least one area: LLM application development, model serving, model evaluation and fine-tuning, or coding-agent development.
Ability to design repeatable evaluations, investigate failures and explain trade-offs between quality, response time and cost.
Ability to discuss technical designs and document results in English when collaborating with international teams.

Other Requirement

Experience operating open-weight models with frameworks such as vLLM or SGLang, including load testing and GPU memory optimisation.
Experience fine-tuning models with domain-specific data and validating improvements on test data kept separate from training.
Experience building document-grounded retrieval systems or coding agents integrated with repositories and automated tests.

We Care More About How You Work and Live

Some things are simply essential: MacBook Pro, large monitor, Sony noise-cancelling headphones, snacks, coffee and fresh fruit.Some rewards are simply standard: holiday bonuses, , quarterly performance bonuses, and referral bonuses.

But what matters even more to us:

Flexible work hours & hybrid work
Annual health check-ups, gym subsidy & monthly massages
A nap room — because proper rest matters
Learning & development allowance
Team lunches, employee clubs & activities
12 weeks maternity leave & 14 days prenatal and paternity leave
Annual Company Retreat — from Dubai and Phuket to Bali, Vietnam and Cebu
Fully covered employee portion of Labor & National Health Insurance
Enterprise AI tools, including ChatGPT

Great work matters. So does having a life outside of it. If that sounds like your kind of workplace, we’d love to meet you.

About the Company

OpenNet

Develops mobile sports entertainment apps

OpenNet develops and deploys mobile-first sports entertainment products for global markets. Its product lineup includes online games, video streaming, P2P chat, and integrated FinTech services. In gaming, it creates and validates mathematical models for casino games to ensure fairness and manage risk for regulatory compliance and decision-making. It also strengthens user experience with personalized recommendations powered by advanced algorithms and data mining. Services span technical strategy, UX design, native Android and iOS development, and robust backend development. The goal is to offer end-to-end mobile entertainment solutions worldwide, combining engaging apps with risk management and compliance.

Company size: 51-200
Company stage: Not listed
Total funding: Not listed
Headquarters: Taipei, Taiwan
Founded: 2019

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