Senior Machine Learning Research Engineer (AI)

TL;DR

Senior Machine Learning Research Engineer (AI): Exploring, reproducing, and validating cutting-edge ML methodologies for real-world AI product development with an accent on academic paper analysis, benchmark dataset construction, and model evaluation. Focus on building measurable prototypes under practical compute constraints and bridging the gap between research and production-ready AI solutions.

Location: Must be based in EU countries

Company

hirify.global is a global provider of business and tech advisory, enterprise solutions, and product development services with over 6000 specialists.

What you will do

• Read and analyze scientific ML papers to identify promising methodologies for reproduction.
• Build and validate PoCs based on academic research and open-source implementations.
• Debug and adapt research repositories to function under practical compute constraints.
• Curate and construct benchmark datasets to test specific ML methodologies.
• Build evaluation pipelines to compare replicated approaches against strong baselines.
• Collaborate with AI engineers to translate research findings into practical project directions.

Requirements

• Must be based in EU countries
• Strong machine learning fundamentals with hands-on experience in applied research.
• Proven ability to dissect academic papers and debug open-source research repositories.
• Experience identifying, curating, and constructing benchmark datasets.
• Strong Python skills and proficiency with modern deep learning frameworks.
• Practical understanding of model evaluation, metrics, and error analysis.

Nice to have

• Experience with LLMs, agentic systems, or tool-based AI workflows.
• Background in MLOps, experiment tracking, or reproducible ML pipelines.
• Experience building rigorous evaluation pipelines from scratch.
• Academic publications, PhD, or significant open-source research contributions.

Culture & Benefits

• Commitment to equal opportunities and diversity in the workplace.
• Focus on professional growth and career development.
• Collaborative environment working on cutting-edge AI research and development.
• Global company structure with a focus on human-centric technology.

Hiring process

• Application review by the talent team.
• Talent acquisition interview to discuss goals and company fit.
• Technical interview focusing on problem-solving and expertise.
• Potential customer interview for project alignment.