Machine Learning Engineer

PLAY, GROW and WIN

To be a part of Virtuos means to be a creator.  

At Virtuos, we harness the latest technologies to make games better and more immersive than ever before. That is why we pride ourselves in constantly pushing the boundaries of possibility since our founding in 2004. 

Virtuosi is a team of experts – people who have come together to share their mutual passion for making and playing games. People with the same enthusiasm for exploring new ideas and the constant drive to excel in their field. People who believe in earning success through dedication.

At Virtuos, we are at the forefront of gaming, creating exciting new experiences daily. Join us to Play, Grow and Win – together.

ABOUT THE POSITION

We are seeking a highly skilled and motivated Machine Learning Engineer with expertise in computer vision, large language models (LLMs), and the deployment and serving of machine learning models. As a part of our AI/ML team, you will work on cutting-edge projects, leveraging state-of-the-art machine learning techniques to develop, deploy, and scale models that drive innovation in our product offerings.

• Design, develop, and implement machine learning models with a focus on computer vision models, large language models (LLMs), Vision large language models (vLLMs), AI Agent for multi-modal tasks and applications.
• Collaborate with stakeholders, software engineers, and product teams to define problems, develop solutions, build proof of concepts, conduct experiments, and deploy models into production using modern tools and best practices
• Ensure scalability, efficiency, and performance in model deployment and serving across cloud and on-premise infrastructure.
• Develop and maintain automated pipelines for model training, validation, and deployment.
• Perform regular model evaluations, troubleshooting, and optimization to ensure models perform at peak efficiency.
• Keep up to date with the latest advancements in AI/ML, especially in computer vision and natural language processing (NLP), and recommend integration of new techniques.

• Bachelor's or Master's degree in Computer Science, Machine Learning, or related fields. 
• 3+ years of hands-on experience in machine learning and deep learning, with a focus on computer vision and large language models.
• Proficiency in frameworks like PyTorch or Tensorflow for building and training deep learning models.
• Proficiency in Data ETL framework such as Pyspark, BigQuery, Presto for distributed cloud and on-premise data processing.
• Proficiency in frameworks such as FastAPI for building efficient APIs and tools like Langchain (or similar frameworks) for integrating large language models into applications
• Strong experience in developing models for computer vision and multimodal tasks such as image classification, object detection, segmentation, image generation etc
• Familiarity with common SQL databases (e.g., PostgreSQL), NoSQL databases (e.g., MongoDB) and Vector databases (e.g Weaviate) for efficient data storage, retrieval, and management
• Familiarity with Docker
• Solid understanding of Data Science development process, software development principles, including CI/CD, version control (e.g., Git), and best practices for code quality.
• Experience with MLOps tools and workflows to ensure reproducibility, automation, and monitoring of models in production.
• Strong problem-solving skills and the ability to work independently and collaboratively in a fast-paced environment. 

• Experience with multi-modal machine learning combining computer vision and natural language understanding
• Experience with optimization techniques for model inference, such as quantization, pruning, or model distillation.
• Experience with building either search and recommendation applications or generative AI applications
• Familiarity with data labeling and management tools for computer vision and NLP datasets.
• Familiarity with AWS services
• Familiarity with designing end to end ML system
• Fluent with English
• Experience in reproducing and implementing models from research papers, to adapt and optimize them for real-world applications is a plus
• Knowledge in art and game production processes, or developing ML solutions for game production is a plus
• Contributions to open-source machine learning libraries or research publications in AI/ML is a plus