LLM Engineer

Summary

Join Sporty, a leading sports betting website with millions of weekly active users, as a Data Scientist. You will develop innovative data science solutions and machine learning models to drive business impact, collaborating closely with Trading, Product, and Tech teams. Leverage your expertise to translate business challenges into supervised and/or unsupervised learning problems. Sporty Group is a global consumer internet and technology business with a diverse team of 300+ high achievers. We offer a dynamic and flexible work environment that empowers employees and rewards contributions generously. This role involves owning the full LLM lifecycle, building evaluation pipelines, integrating LLM services, and partnering with product and engineering teams. You will also monitor models, manage versioning, and mentor teammates.

Requirements

• 2+ years in data science, ML, or software dev, including 6+ months hands-on with GPT-style models
• Proficient in core Python and key AI libraries (transformers, LangChain/LlamaIndex, FastAPI/Flask)
• Demonstrated skill in prompt engineering and parameter-efficient fine-tuning (e.g., LoRA, PEFT)
• Experience designing and running evaluation frameworks for relevance, safety, and ROI
• Familiarity with vector databases (Pinecone, FAISS, Milvus) and API integration patterns
• Strong communication and collaboration abilities in fast-moving, cross-functional teams

Responsibilities

• Own the full LLM lifecycle—prompt design, data prep, fine-tuning, deployment, and continuous optimization
• Build automated and human-in-the-loop evaluation pipelines to track quality, safety, and business KPIs
• Integrate LLM services into products via REST/GraphQL APIs and vector-database retrieval
• Partner with product and engineering to turn business problems into AI features that boost revenue and user engagement
• Monitor models in production, manage versioning/rollback, and lead basic MLOps workflows
• Evangelize best practices and mentor teammates on emerging LLM tools and responsible AI

Preferred Qualifications

• Exposure to MLOps tooling such as Docker, MLflow, GitHub Actions, or Hugging Face Hub
• Knowledge of retrieval-augmented generation (RAG) architectures and embedding techniques
• Track record of shipping AI features in production SaaS, gaming, or fintech environments
• Understanding of A/B testing and product analytics to measure model impact
• Cloud experience on AWS, GCP, or Azure, especially managed AI/DB services
• Interest or background in quantitative methods or casino-gaming analytics

Benefits

• Quarterly bonuses
• We have core hours of 10am-3pm in a local timezone, but flexible hours outside of this
• Top-of-the-line equipment
• Referral bonuses
• 28 days paid annual leave
• Annual company retreat
• Highly talented, dependable co-workers in a global, multicultural organisation
• Payment via DEEL, a world class online wallet system
• Our teams are small enough for you to be impactful
• Our business is globally established and successful, offering stability and security to our Team Members