Staff Machine Learning Engineer

NLP PEOPLE; Cuneo; In loco; EUR 70.000 - 120.000; Tempo pieno

Descrizione del lavoro

A leading company in sports technology is seeking a Staff Machine Learning Engineer to drive the development of innovative AI solutions. The ideal candidate will have significant experience in backend engineering, especially with ML algorithms. Join a diverse team dedicated to enhancing sports betting technologies globally.

Competenze

• 10+ years experience as a Software Engineer focused on distributed systems.
• Proficiency in backend languages like Python, C#, and Go.
• Experience with AI / Machine Learning applications.

Mansioni

• Design and implement scalable AI solutions.
• Collaborate to integrate machine learning models.
• Take ownership of code quality and documentation.

Conoscenze

Python

C#

Data structures

Machine Learning

Algorithms

Git

Strumenti

PostgreSQL

GCP

Docker

Kubernetes

Descrizione del lavoro

Sportserve forms part of a remarkable group of B2C sports betting and B2B sportsbook technology companies, focused on delivering first class sports betting experiences and casino products for our users worldwide. Along with Sportion, TechSpirit, Standard Focus and Sportelligent, we are the driving force behind the world renowned sports betting company and our flagship brand, Dafabet.

Since launching our global hiring initiative, we now employ over 2,000 people worldwide, offering exciting career paths in Technology, Trading, Operations and Media. We pride ourselves on having a diverse and international culture that embraces the global community and acts locally. We offer office based, hybrid and remote work on permanent and consultancy contracts all over the world, making us the true global employer of choice.

As a Staff Machine Learning Engineer with a backend focus, you will play a pivotal role in shaping scalable AI and algorithmic solutions that directly address complex business challenges. You are expected to possess a deep understanding of both the technical and domain-specific landscapes, enabling you to architect robust systems that integrate seamlessly with our platforms.

You will be part of a high-impact team that works at the intersection of data, machine learning, and backend engineering.

What you’ll be getting up to :

• Design and implement efficient, scalable solutions that support advanced algorithmic and AI / Machine Learning-driven applications.
• Define and architect solutions that are structurally sound and align with best practices, ensuring robust integration with data-driven systems.
• Collaborate with various departments to integrate machine learning models and complex algorithms into business driven applications.
• Support and improve existing AI / Machine Learning solutions
• Take ownership of code quality, testing, and documentation to maintain high standards and continuous improvement across projects.
• Stay engaged in new technologies, AI advancements, and domain-specific knowledge, bringing fresh insights and approaches to the team.

Required Technical Skills

• 10+ years experience as a Software Engineer with a focus on high throughput distributed systems with a focus on the backend.
• Proven experience in backend development with proficiency in languages such as Python, C# on Linux, Go, or similar.
• Utilise Advanced Technical Stack : Leverage our technical stack, including Python, SQL, PostgreSQL, BigQuery, and libraries such as Pandas, NumPy, SciKit-Learn, XGBoost, Matplotlib, and Pytorch, to develop robust and scalable AI / ML solutions.
• Strong foundation in data structures, algorithms, and problem-solving, with a clear focus on efficiency and optimisation.
• Experience with architecting and implementing large-scale, distributed systems that handle significant data processing.
• Apply knowledge of Large Language Models (LLMs) such as OpenAI’s GPT models, Claude, Gemini, Llama, Whisper, and Groq to develop innovative Gen AI use cases and solutions.
• Knowledge of databases (SQL and NoSQL) and experience in designing data storage solutions that support machine learning workflows.
• Advanced experience with PostgreSQL (stored procedures, functions, views, etc.).
• Fluent with GCP cloud platform and containerization tools (e.g., Docker, Kubernetes).
• Implement and optimise CI / CD pipelines for machine learning model deployment using Gitlab CI.
• Monitor system performance and implement improvements for scalability.
• Participate in code reviews and technical documentation.
• Experience with version control systems (Git) and collaborative development workflows.

Requirements :

• Passion for continuous learning and a keen interest in exploring and mastering new domains, especially in AI / ML and data-driven technologies.
• Strong analytical skills and an ability to translate complex problems into effective, scalable solutions.
• Excellent communication skills to effectively collaborate with cross-functional teams and articulate technical concepts to diverse stakeholders.
• Excellent command of the English language – written & spoken.
• Attention to detail and commitment to quality.
• Collaborative team player.
• Highly organised with a strong ability to prioritise across multiple projects.
• We warmly invite applications in English.

Diversity & Inclusion at Sportserve

At Sportserve, we are deeply committed to fostering a diverse and inclusive workplace. We believe in building a team that reflects a wide array of backgrounds, skills, and perspectives. Embracing diversity not only enriches our work culture but also drives innovation and excellence. We are proud to be an equal opportunity employer, where everyone’s contribution is valued and respected.

If you’re a passionate about technology and looking to start your career in an international, forward-thinking Sports Betting company, we’d love to hear from you. Apply now to become part of our exciting journey!

Company : Sportserve

Qualifications : Language requirements : Specific requirements : Educational level : Level of experience (years) :

Senior (5+ years of experience)

Tagged as : Industry, Italy, Language Modeling, Machine Learning, NLP

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