Senior Machine Learning Scientist (AI)

TL;DR

Senior Machine Learning Scientist (AI): Building and optimizing the ML models that power metasearch bidding and auction strategies across key partners with an accent on end-to-end ML solutions and technical leadership. Focus on designing and implementing production-grade ML models, enhancing experimentation strategies, and influencing domain roadmaps through cross-functional collaboration.

Location: Hybrid in London, United Kingdom

Company

hirify.global is a global travel technology company designing cutting-edge solutions for travel and partners.

What you will do

• Own end-to-end ML solutions within your domain, from problem framing through deployment and post-launch iteration.
• Define technical direction for your area, including model architecture, system design, and data contracts.
• Lead multi-quarter ML initiatives in partnership with engineering, product, and business stakeholders.
• Design and implement production-grade ML models (e.g., gradient-boosted trees, deep learning, optimization algorithms, bandits/RL policies).
• Build robust training, evaluation, and serving pipelines with embedded observability and failure handling.
• Enhance experimentation and measurement strategies, including A/B tests and causal inference methods.

Requirements

• Master’s or PhD in Computer Science, Statistics, Applied Mathematics, Operations Research, or equivalent industry experience.
• 6+ years (Master’s) or 4+ years (PhD) of hands-on experience applying machine learning to real-world problems.
• Demonstrated track record of leading at least one complex, multi-stakeholder production ML initiative.
• Deep ML expertise in supervised and unsupervised learning, including tree-based methods and deep learning.
• Strong experimentation and statistics skills, including designing and interpreting A/B tests and applying causal inference techniques.
• Fluency in Python and core data/ML libraries (pandas, NumPy, scikit-learn, PyTorch or TensorFlow), combined with solid software engineering practices.
• Proficient with large-scale data, strong SQL skills, and familiarity with distributed data processing (e.g., Spark, Hive).

Nice to have

• Experience with ads, auctions, marketplace optimization, or bidding systems.
• Familiarity with multi-objective or constrained optimization problems.
• Hands-on experience with modern ML production practices: feature stores, model registries, CI/CD for ML, automated monitoring and alerting.
• Experience shaping team-level technical direction.
• Exposure to causal inference or advanced experimentation techniques in noisy business environments.
• Experience with AI/ML-driven systems, including exposure to large language models or foundation model fine-tuning and evaluation.

Culture & Benefits

• Open culture guided by Values and Leadership Agreements where everyone belongs.
• Full benefits package, including travel perks and generous time-off.
• Parental leave and a flexible work model.
• Career development resources to fuel passion for travel.
• Named a Best Place to Work on Glassdoor in 2024.