LLM Engineer
We consistently top the charts as one of if not the most used Sports Betting website in the countries we operate in.
With millions of weekly active users, we strive to be the best in industry for our users.
As a Data Scientist at Sporty, you will play a vital role in developing innovative data science solutions and machine learning models to drive business impact. Working closely with our Trading, Product, and Tech teams, you will leverage your expertise to tackle a wide range of business challenges, translating them into supervised and/or unsupervised learning problems.
Who We Are
Sporty Group is a consumer internet and technology business with an unrivalled sports media, gaming, social and fintech platform which serves millions of daily active users across the globe via technology and operations hubs across more than 10 countries and 3 continents.
The recipe for our success is to discover intelligent and energetic people, who are passionate about our products and serving our users, and attract and retain them with a dynamic and flexible work life which empowers them to create value and rewards them generously based upon their contribution.
We have already built a capable and proven team of 300+ high achievers from a diverse set of backgrounds and we are looking for more talented individuals to drive further growth and contribute to the innovation, creativity and hard work that currently serves our users further via their grit and innovation.
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.
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.
Nice to have
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
Our Mission
Our mission is to be an everyday entertainment platform for everyone
Our Operating Principles
1. Create Value for Users
2. Act in the Long-Term Interests of Sporty
3. Focus on Product Improvements & Innovation
4. Be Responsible
5. Preserve Integrity & Honesty
6. Respect Confidentiality & Privacy
7. Ensure Stability, Security & Scalability
8. Work Hard with Passion & Pride
Interview Process
Remote video screening with our Talent Acquisition Team
Offline Take home assignment
Remote video interview with Team Members (60 Mins)
Final discussion with the hiring manager (60 mins).
Post Interview Process
Feedback call on successful interview
Offer released followed by contract
ID Check Via Zinc & 2 references from previous employers
Working at Sporty
The top-down mentality at Sporty is high performance based, meaning we trust you to do your job with an emphasis on support to help you achieve, grow and de-block any issues when they're in your way.
Generally employees can choose their own hours, as long as they are collaborating and doing stand-ups etc. The emphasis is really on results.
As we are a highly structured and established company we are able to offer the security and support of a global business with the allure of a startup environment. Sporty is independently managed and financed, meaning we don’t have arbitrary shareholder or VC targets to cater to.
We literally build, spend and make decisions based on the ethos of building THE best platform of its kind. We are truly a tech company to the core and take excellent care of our Team Members.
LLM Engineer
We consistently top the charts as one of if not the most used Sports Betting website in the countries we operate in.
With millions of weekly active users, we strive to be the best in industry for our users.
As a Data Scientist at Sporty, you will play a vital role in developing innovative data science solutions and machine learning models to drive business impact. Working closely with our Trading, Product, and Tech teams, you will leverage your expertise to tackle a wide range of business challenges, translating them into supervised and/or unsupervised learning problems.
Who We Are
Sporty Group is a consumer internet and technology business with an unrivalled sports media, gaming, social and fintech platform which serves millions of daily active users across the globe via technology and operations hubs across more than 10 countries and 3 continents.
The recipe for our success is to discover intelligent and energetic people, who are passionate about our products and serving our users, and attract and retain them with a dynamic and flexible work life which empowers them to create value and rewards them generously based upon their contribution.
We have already built a capable and proven team of 300+ high achievers from a diverse set of backgrounds and we are looking for more talented individuals to drive further growth and contribute to the innovation, creativity and hard work that currently serves our users further via their grit and innovation.
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.
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.
Nice to have
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
Our Mission
Our mission is to be an everyday entertainment platform for everyone
Our Operating Principles
1. Create Value for Users
2. Act in the Long-Term Interests of Sporty
3. Focus on Product Improvements & Innovation
4. Be Responsible
5. Preserve Integrity & Honesty
6. Respect Confidentiality & Privacy
7. Ensure Stability, Security & Scalability
8. Work Hard with Passion & Pride
Interview Process
Remote video screening with our Talent Acquisition Team
Offline Take home assignment
Remote video interview with Team Members (60 Mins)
Final discussion with the hiring manager (60 mins).
Post Interview Process
Feedback call on successful interview
Offer released followed by contract
ID Check Via Zinc & 2 references from previous employers
Working at Sporty
The top-down mentality at Sporty is high performance based, meaning we trust you to do your job with an emphasis on support to help you achieve, grow and de-block any issues when they're in your way.
Generally employees can choose their own hours, as long as they are collaborating and doing stand-ups etc. The emphasis is really on results.
As we are a highly structured and established company we are able to offer the security and support of a global business with the allure of a startup environment. Sporty is independently managed and financed, meaning we don’t have arbitrary shareholder or VC targets to cater to.
We literally build, spend and make decisions based on the ethos of building THE best platform of its kind. We are truly a tech company to the core and take excellent care of our Team Members.