3 months ago
Responsibilities
- Research, prototype, evaluate, and productionize agent capabilities such as memory, planning, tool use, workflow execution, reasoning, and context management.
- Build retrieval systems, memory systems, tool-calling pipelines, workflow orchestration, and agentic reasoning capabilities.
- Train, fine-tune, and adapt LLMs and related models for production use cases when appropriate.
- Build data pipelines for model training, agent evaluation, labeling, dataset construction, quality checks, and feedback loops.
- Design evaluation systems covering task completion, accuracy, latency, cost, reliability, safety, customer experience quality, and regressions.
- Optimize production inference through model selection, serving architecture, batching, caching, latency, throughput, and cost improvements.
- Integrate voice AI, internal tools, third-party APIs, and workflow systems into customer journeys.
- Collaborate with product managers, engineers, and customer-facing teams to deliver shippable AI-agent features.
Requirements
- 5+ years of professional experience in ML engineering, machine learning, data science, or backend engineering with substantial AI/ML ownership.
- Experience building AI-powered product features for real users, preferably involving agents, conversational AI, workflow automation, retrieval, or LLM systems.
- Hands-on experience training, fine-tuning, or adapting LLMs or other deep learning models for production.
- Practical knowledge of model training workflows, including dataset preparation, experiment tracking, evaluation, model selection, and deployment.
- Experience building production LLM systems such as RAG, tool calling, agents, model orchestration, prompt systems, or evaluation pipelines.
- Strong Python skills and experience building production-grade services.
- Working knowledge of inference and serving tradeoffs, including latency, throughput, GPU utilization, model size, batching, caching, and cost.
- Experience with ML infrastructure or MLOps tools for data pipelines, training jobs, model deployment, monitoring, or evaluation.
- Strong debugging ability for agent failures, hallucinations, retrieval quality, model behavior, tool-use failures, and regressions.
- Clear communication skills for explaining technical tradeoffs to product managers, engineers, and leadership.
- Nice-to-have experience with natural language processing, conversational AI, voice AI, large-scale data processing, labeling systems, human feedback workflows, synthetic data generation, GPU infrastructure, or cloud platforms.
- Bilingual fluency in Korean and English is a nice-to-have.
Benefits
- Hybrid work policy with flexible work hours and a minimum of three team office days per week.
- Silicon Valley equity program with a 1-year cliff.
- 3.9 million won prorated professional and personal wellness expense benefit.
- Up to 3.6 million won per year for language lessons.
- Weekly team lunches, monthly team-building support, and partial commuting-cost support.
- Free parking at the Seolleung office.
- Group insurance support for employees, spouses, and children.
- Medical checkup support for employees and one family member.
- Seven additional paid holidays beyond annual leave.
- Support for current work devices such as MacBook Pro.
- Daily snacks, beverages, and instant noodles.
- 12-week paid parental leave for mothers and fathers.
- Additional congratulations and condolences support programs.
Tech Stack
Categories
About Sendbird
Sendbird is the AI customer experience company. We provide the infrastructure that powers delight.ai – the branded AI concierge, and the Sendbird Communication Suite, the world’s #1 communication API platform. Together, they enable brands to deepen connection and deliver personal, trusted, and unforgettable customer experiences. Trusted by 4,000+ leading brands—including DoorDash, Match Group, Noom, and Yahoo Sports—Sendbird powers over 7 billion conversations every month, offering exceptional reliability, security, and compliance that meet enterprise-level demands. Headquartered in California, Sendbird is backed by ICONIQ, SoftBank, Tiger Global, Y Combinator, and other reputable investors.