Senior Machine Learning Research Engineer (AI)

TL;DR

Senior Machine Learning Research Engineer (AI): Exploring, reproducing, and benchmarking cutting-edge ML methodologies to validate research papers for real-world AI product development with an accent on paper replication and ground truth data creation. Focus on building measurable prototypes under practical compute constraints and developing rigorous evaluation pipelines.

Location: Fully Remote (Poland)

Company

A global provider of tech advisory, enterprise solutions, and software development services with over 6000 specialists.

What you will do

• Analyze scientific ML papers to identify and reproduce promising methodologies.
• Build PoCs and debug open-source research repositories under practical compute constraints.
• Curate and construct benchmark datasets and prepare ground truth data for validation.
• Develop evaluation pipelines to compare replicated approaches against baselines.
• Document experiment results, limitations, and recommendations for product direction.
• Collaborate with AI engineers and stakeholders to transition research into practical implementation.

Requirements

• Strong machine learning fundamentals and experience with applied research projects.
• Proven ability to dissect academic papers and replicate research results.
• Proficiency in Python and modern deep learning frameworks.
• Expertise in model evaluation, metrics, error analysis, and reproducibility.
• Ability to work independently in ambiguous R&D / PoC environments.
• Must be based in Poland

Nice to have

• Experience with LLMs, agentic systems, or tool-based AI workflows.
• Knowledge of MLOps, experiment tracking, and model versioning.
• Background in data annotation and benchmark design.
• PhD, research publications, or significant open-source contributions.

Culture & Benefits

• Equal opportunity environment focusing on diversity and inclusion.
• Opportunities for career development and leadership.
• Supportive team culture in a fast-moving R&D setup.

Hiring process

• Application review followed by a Talent Acquisition interview.
• Technical interview focusing on problem-solving and expertise.
• Optional customer interview for alignment.