Manager AI/ML

Location: Budapest (Flexible), Hungary; remote work options available.

Company

hirify.global provides an AI-powered experience orchestration platform connecting people, systems, data, and AI for more than 8,000 organizations in over 100 countries.

What you will do

• Lead a small to mid-sized team of AI Engineers, Data Scientists, and software engineers; plan resourcing, hiring, performance reviews, coaching, and career development.
• Guide research teams building, training, and deploying their own models from problem framing and dataset preparation through experimentation, evaluation, and production operation.
• Oversee solutions featuring LLMs and LAMs, including fine-tuning, distillation, open-weight model adaptation, prompt and context engineering, retrieval-augmented generation, agentic workflows, and generative-system evaluation.
• Address complex technical and quantitative problems across diverse datasets and develop methods and evaluation criteria using independent judgment.
• Present results and explain AI and data science concepts and tradeoffs to technical and non-technical audiences while partnering with PM, UX, and other stakeholders.
• Architect scalable AI and data platforms on AWS and ensure secure, reliable, fair, and responsible AI behavior.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, Engineering, or a related field, or equivalent experience, with 8–10 years of relevant experience.
• Proven leadership of AI/ML or data science teams and ability to direct and review the work of experienced professionals.
• Experience overseeing research teams that built, trained, and deployed their own models into production across the full lifecycle from problem definition and dataset preparation through experimentation, evaluation, and operation.
• Direct experience overseeing teams delivering LLM and/or LAM solutions through fine-tuning, distillation, and combining or adapting open-weight models, with supporting work in prompt and context engineering, retrieval-augmented generation, agentic workflows, and generative-system evaluation.
• Strong grounding in machine learning, statistical methods, model development and evaluation, and the tradeoffs of deploying models at scale.
• Hands-on MLOps experience with experiment tracking, model CI/CD, and monitoring for drift and performance.
• Proficiency in Python and relevant frameworks such as PyTorch, TensorFlow, scikit-learn, and Hugging Face.
• Ability to architect scalable and robust AI and data platforms on AWS, including microservices, RESTful APIs, serverless systems, Kafka, and GPU/compute infrastructure.
• Ability to manage technical projects through delegation and review, collaborate with cross-functional partners, and apply responsible AI practices.

Nice to have

• Deep understanding of modern deep learning and generative AI architectures, large-scale training or fine-tuning, and model evaluation, safety, and alignment techniques.
• Publications, patents, open-source contributions, or experience taking novel research from idea to deployed product.
• Experience with data pipelines, feature stores, vector databases, and data governance practices for production AI.
• Experience contributing to HLA/HLD documents, leading cross-team design discussions, and making architectural decisions for enterprise-scale AI systems.
• Collaborative mindset with commitment to psychological safety, inclusion, and high performance.

Culture & Benefits

• Flexible-first culture with remote work options.
• Continuous learning in management and emerging AI technologies, including mentorship, learning programs, leadership development, and education support.
• Clear advancement paths toward senior leadership roles.
• Mutual support, work-life balance, and professional growth.
• Paid volunteer time, August Free Fridays, well-being resources, and regionally tailored programs for employees and their families.

Hiring process

• Talent Acquisition and the hiring team review the application.
• Qualified candidates complete a Zoom interview, followed by interviews with the hiring manager and other interviewers.
• The process typically includes no more than five interviews, followed by final steps.