Machine Learning Engineer (Agent & Inference) - (Chinese Mandarin Speaker)

Bitus Labs is seeking a Machine Learning Engineer to join the AI Engineering team, focusing on agent systems and production inference for an online gaming product. The role emphasizes designing LLM powered agents, memory and RAG pipelines, vector-store infrastructure, and production inference, with fluency in Mandarin Chinese required.

Benefits and culture

• 401(k)
• 401(k) matching
• Dental insurance
• Health insurance
• Life insurance
• Paid time off
• Parental leave
• Retirement plan
• Vision insurance

Salary

USD 130,000 per year

Location and work setup

• Irvine, CA 92618 (onsite; in-person work)
• Relocation to Irvine, CA 92618 before start date (required)

Responsibilities

• Architect and refine LLM driven agents, including planning, tool integration, workflow orchestration, and multi-step reasoning
• Design memory systems for short-term and long-term storage, context management, and session state
• Develop and optimize retrieval augmented generation pipelines for relevance, grounding, freshness, and retrieval quality
• Build and operate vector-store infrastructure using pgvector, Milvus, Qdrant, or Weaviate
• Define evaluation methodologies for agents, prompts, and workflows
• Improve end-to-end agent quality, latency, reliability, and operating cost
• Develop and run production inference services that are low-latency, high-concurrency, and highly reliable
• Support online-learning models such as contextual bandits and reinforcement learning policies with real-time inference and online parameter updates
• Deploy and optimize AI inference systems for latency, throughput, reliability, and resource efficiency
• Analyze and resolve inference-serving bottlenecks
• Assist in deployment and serving of recommendation, ranking, and RL models created by research scientists
• Apply lightweight model adaptation techniques such as LoRA, QLoRA, and PEFT when appropriate for domain needs
• Build and maintain deployment pipelines, observability systems, and tracing infrastructure for agents and serving endpoints
• Monitor quality regression, performance degradation, and model drift
• Maintain version control for models, prompts, datasets, and agent configurations
• Contribute to automated validation, testing, and CI/CD workflows for AI systems
• Collaborate with research scientists, backend engineers, and data scientists to integrate AI systems into production products
• Document systems, best practices, and internal tooling
• Contribute to engineering standards and operational excellence across AI initiatives

Requirements

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, or a related field
• 3+ years of industry experience in Machine Learning Engineering or related roles
• Strong software and systems engineering experience building low-latency, reliable production services in Go, Rust, C++, or equivalent
• Experience with real-time inference systems for recommendation, ranking, contextual bandits, reinforcement learning, or similar adaptive ML applications
• Strong experience with PyTorch and the Hugging Face ecosystem
• Experience building production LLM or agent applications (e.g., LangGraph, LlamaIndex, or equivalent frameworks)
• Hands-on experience with RAG systems, embeddings, and vector databases
• Experience evaluating and monitoring LLM or agent systems in production
• Experience deploying and optimizing production machine learning or LLM systems
• Understanding of inference runtime behavior, resource utilization, latency optimization, and production serving performance
• Experience with Docker and Kubernetes
• Experience with cloud platforms such as AWS, GCP, or Azure
• Fluent Mandarin Chinese

Technologies

• Go
• Rust
• C++
• PyTorch
• Hugging Face
• LangGraph
• LlamaIndex
• pgvector
• Milvus
• Qdrant
• Weaviate
• Docker
• Kubernetes
• AWS
• GCP
• Azure
• LoRA
• QLoRA
• PEFT
• CUDA
• OpenAI Triton
• TFLite
• CoreML
• FSDP
• DeepSpeed
• Spark
• Hadoop