Senior LLM Scientist
Job Summary
Job Description
The Senior LLM Scientist will be responsible for developing end-to-end solutions, from defining problems to deploying models into production. This involves collaborating with product teams, working closely with ML engineers, conducting evaluations, and staying updated on the latest research. They will work on LLM-related topics like agents, chatbots, and RAG systems. The role requires building and deploying enterprise-level LLM applications and a strong understanding of evaluation techniques, reasoning, and workflows. They will also be involved in mentoring junior scientists. The role requires a Master's or PhD degree in a related field and experience in machine learning or engineering roles. Experience in cross-functional collaboration and leading projects is also required. A strong sense of impact, excellent analytical skills and a passion for new technologies are also important.
Must have:
- 3+ years of experience in machine learning roles
- Experience in building and deploying LLM applications
- Familiar with LLM evaluation techniques
- Experience in multi-step reasoning and workflows
- Experience in cross-functional collaboration
Good to have:
- Industry experience in the MarTech domain
- Experience with LLM toolkits or frameworks
- Familiarity with prototyping tools
- Knowledge of fine-tuning or adaptation techniques
8 skills required
Job Details
About Appier
Appier is a software-as-a-service (SaaS) company that uses artificial intelligence (AI) to power business decision-making. Founded in 2012 with a vision of democratizing AI, Appier’s mission is turning AI into ROI by making software intelligent. Appier now has 17 offices across APAC, Europe and U.S., and is listed on the Tokyo Stock Exchange (Ticker number: 4180). Visit www.appier.com for more information.
About the Role
We are looking for a Senior LLM Scientist to join the Enterprise Solution Science Team.
This team focuses on applying cutting-edge ML technologies to real-world marketing problems by combining them with omnichannel customer data.
In this role, you will be responsible for end-to-end development, from problem definition to driving model deployment into production.
What You’ll Work On
- Work on one or more of the following LLM-related topics: agents, chatbots, copilots, RAG systems
- Collaborate with product teams to translate product goals and business needs into well-defined ML problems during the planning stage
- Work closely with ML engineers to deploy models to production, ensuring reliability and maintainability
- Conduct offline and online evaluation, monitoring, and continuous optimization of models after deployment
- Stay up to date with the latest research and proactively propose innovative applications
- (Optional) Mentor junior scientists and help evolve team developing culture and standards.
What We’re Looking For (Minimum)
- Master’s or PhD degree in Computer Science, Machine Learning, Mathematics, Electrical Engineering, or related fields
- 3+ years of experience in machine learning or engineering roles
- Experience in building and deploying enterprise-level LLM applications (e.g., intelligent agents)
- Familiar with LLM evaluation techniques, including hallucination detection and confidence scoring, with an emphasis on quantitative metrics and systematic benchmarking.
- Hands-on experience with multi-step reasoning, modular workflows (e.g., multi-component prompting, agent orchestration), and RAG pipelines
- Experience in cross-functional collaboration and leading industry projects
- Strong sense of impact, with excellent analytical and problem-solving skills, and a passion for new technologies
- Proficient in using LLM-powered tools (e.g., Github Copilot, ChatGPT) to boost development productivity
What We’re Looking For (Preferred)
- Industry experience in the MarTech domain, with a strong passion for building customer-centric products
- Experience with LLM toolkits or frameworks like LangChain, AutoGen, or Google ADK
- Familiarity with prototyping tools such as Streamlit or Gradio
- Knowledge of fine-tuning or adaptation techniques, such as LoRA or instruction tuning
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