Senior Machine Learning Engineer

Location: Dublin, Ireland; hybrid. Core hours are approximately 10:00–18:30 local, with flexibility to start and end late to provide overlap with the US headquarters.

Company

hirify.global develops and publishes video games, including NBA hirify.global, BioShock, Borderlands, Mafia, Sid Meier’s Civilization, XCOM, and other major franchises through a portfolio of global game development studios.

What you will do

• Deploy ML models as production-grade decision services and integrate them into games and live products.
• Own and mature MLOps practices, including CI/CD, model registries, feature stores, inference, monitoring, drift detection, and reproducibility.
• Design and prototype ML-powered products for recommendations, matchmaking, cheat and toxicity intervention, and economy balancing.
• Plan and execute ML application integrations with studio developers and central technology teams for game launches.
• Evaluate and pilot GenAI and LLM use cases, turning promising concepts into secure, scalable, and measurable solutions.

Requirements

• Bachelor’s degree in Computer Science, Computer or Electrical Engineering, or a related STEM field with 4+ years of software engineering experience, including substantial production ML deployment experience; alternatively, a Master’s degree with 2–4 years of relevant experience.
• Strong programming skills and proficiency in Python; experience with a high-performance systems language such as C, C++, Java, or Rust is beneficial.
• Knowledge of supervised and unsupervised ML tasks, common traditional and deep learning algorithms, and the end-to-end ML lifecycle.
• Hands-on experience with PyTorch, TensorFlow, scikit-learn, or Spark ML.
• Production experience with AWS, GCP, or Azure; containers, Kubernetes, serverless systems, and microservice architecture.
• Experience with MLOps, CI/CD, model registries, feature stores, pipeline orchestration, automated training and deployment, monitoring, databases, Apache Spark, or lakehouse technologies.

Nice to have

• Experience with recommender systems, search, matchmaking, reinforcement learning, infrastructure as code, or managed ML platforms.
• Familiarity with Apache Kafka, Kinesis, Spark Streaming, GenAI, LLM applications, RAG, evaluation, guardrails, agentic workflows, vector databases, Unreal, or Unity.

Culture & Benefits

• Work in an inclusive environment that supports diverse perspectives and encourages employees to contribute authentically.
• Collaborate with ML scientists, data engineers, central technology teams, and game studios.
• Participate in work supporting major game franchises and live products across multiple platforms.
• Reasonable accommodation is available for qualified individuals with disabilities during hiring and employment.