№ 1003 · Sports betting analytics · Remote Archived
ML Engineer (LLM) at a sports betting and gaming analytics tech company — remote or hybrid
The ML Engineer (LLM) will fine-tune, optimize and deploy LLM-powered solutions across the business.
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About the company
A tech company in the sports betting and gaming analytics space is expanding its internal AI team and is looking for a Senior ML Engineer with experience in Large Language Models.
You will be working on LLM-powered solutions to enhance various aspects of the business, including customer support automation, content generation, and decision support systems. The role involves fine-tuning, optimizing, and deploying LLMs for real-world applications in the sports betting industry.
What you will do
- Develop and fine-tune LLMs for a range of applications within the company.
- Optimize model inference to ensure quick and efficient response times in production.
- Build and enhance retrieval-augmented generation (RAG) pipelines.
- Create and manage evaluation workflows to measure model performance and consistency.
- Deploy models in scalable, production-ready environments, ensuring stability and robustness.
- Collaborate with software engineers to integrate LLM-based APIs into company products.
- Keep up with the latest advancements in research and implement best practices in LLM development.
What matters
- Experience fine-tuning and deploying LLMs in real-world applications.
- Proficiency in Python and hands-on experience with Hugging Face Transformers and either PyTorch or TensorFlow.
- Experience with major LLM APIs (OpenAI, Anthropic, Claude, Gemini, etc.) and/or open-source models (LLaMA, Mistral, Falcon).
- Solid understanding of LLM architecture, prompt engineering, and text generation evaluation methods.
- Basic knowledge or practical experience with retrieval-augmented generation (RAG) and LLM-based search.
- Familiarity with model optimization techniques (quantization, distillation) is a plus.
- Strong coding skills with attention to clean code, testing, and CI/CD practices.
- Experience with Docker and Kubernetes; cloud platforms like AWS, GCP, or Azure is a plus.
- Proactive mindset with a willingness to take ownership and grow in the LLM domain.
Terms
- Employment under an employment or service contract, depending on the candidate's location.
- Remote or hybrid work format.
- Flexible working hours and additional vacation days.
- Open and supportive corporate culture with a friendly atmosphere.
- Equipment provided for work.
- Development and training opportunities: language course reimbursement, access to educational programs.