Lead AI Scientist (AI)

Location: On-site in Kraków, Poland

Company

hirify.global is a global science and technology company operating across life sciences, diagnostics, biotechnology, and related businesses.

What you will do

• Evaluate and operationalise emerging AI methodologies, models, architectures, frameworks, and technologies.
• Design experiments, benchmarks, evaluations, and proof-of-concepts to assess enterprise AI adoption.
• Develop, prototype, validate, and productise solutions using generative AI, agentic AI, machine learning, reasoning systems, and multimodal AI.
• Translate research findings and technical discoveries into reusable capabilities, reference patterns, working solutions, and practical guidance.
• Collaborate with platform, data, product, architecture, AI engineering, and software engineering teams.

Requirements

• Deep hands-on expertise in modern AI methodologies, generative AI, agentic AI, statistical modelling, and machine learning.
• Strong knowledge of AI architectures, model evaluation, benchmarking, experimentation design, and scientific research practices.
• Experience translating emerging AI technologies and research into practical applications, working solutions, and technical recommendations.
• Strong analytical and problem-solving skills for addressing complex technical challenges.
• Excellent communication and collaboration skills with technical and non-technical audiences.

Nice to have

• Experience in applied AI research, advanced machine learning, generative AI, or emerging AI capability development.
• Experience designing AI evaluation frameworks, benchmarks, experimentation methodologies, or performance assessment approaches.
• Experience translating prototypes and research into reusable enterprise capabilities and production solutions.
• Experience in life sciences, diagnostics, healthcare, advanced manufacturing, or other regulated industries.

Culture & Benefits

• Work within a corporate enterprise AI capability supporting multiple operating companies.
• Collaborate across product, architecture, engineering, data, and operations functions.
• Participate in a culture focused on continuous improvement, innovation, and measurable business impact.
• Develop reusable AI solutions and enterprise standards for science and technology applications.