MLOps Engineer

Sporty – SPORTY Technical /
Full-time /
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 an MLOps Engineer at Sporty, you will be responsible for building robust pipelines that support the entire machine learning lifecycle, encompassing research, iteration, model deployment, low-latency prediction, and model observability. You will play a crucial role in bridging the gap between application software engineering and machine learning/data science, ensuring the seamless integration of our ML solutions across the business.

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.


Create generic CI/CD pipelines for deployment of machine learning models that handles a wide range of scenarios for various parts of our business, on fast and versatile data sources with millions of changes per day
Build pipelines for the full machine learning lifecycle, including model development, model deployment, low-latency prediction, and model monitoring
Connect application software engineering and machine learning/ data science.Implement generic application for ML model serving and orchestration
Develop blueprints for deployment of machine learning and data science projects to work towards MLOps
Write unit, integration, and performance tests for QA
Support data scientists in real on-premise and cloud-based projects


Degree in Computer Science, IT (Information Technology), Engineering, or a related technical field
3+ years of experience as an MLOpsEngineer, Machine Learning Engineer, Data Scientist, or Software Engineer
Strong software engineering skills and experience implementing scalable machine learning solutions in production
General understanding of statistics and machine learning
Good knowledge of relational databases and NoSQL databases
Strong understanding of Python and SQL as primary delivery languages, including design patterns and associated engineering principles
Experience in modern cloud-based platforms, and associated engineering/design principles
Practical exposure to modern data platforms (both cloud and on-premise), with direct experience delivering data centric solutions
Experience with modern engineering approaches (including MLOps) and in working in an engineering role for a data science team/ environment
Understanding of containerization and orchestration technologies like Docker/ Kubernetes
Familiarity with one or more MLOps frameworks (Kubeflow, Apache Airflow, Argo Workflow, MLFlow, etc.)
Experience delivering using agile based approaches, and an ability to operate both as part of a core team, and independently as a subject matter expert
Experience in distributed microservice architecture and REST API development

Nice to have

Experience with Apache Spark
Relevant knowledge or experience in the gaming industry

Quarterly and flash 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

Online HackerRank Test (Max time of 90 Minutes)
Remote video screening with our Talent Acquisition Team 
Remote video interview with 3 x Team Members (45 mins each, not separate days)
24-72 hour feedback loops throughout process

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.