Machine Learning Engineer (AI)

TL;DR

Machine Learning Engineer (AI): Building and optimizing intelligent AI systems across the full lifecycle, from raw data to deployed models and measurable business impact, with an accent on developing solutions for ranking, chatbot, intent recognition, agentic AI, and recommender systems. Focus on applying strong coding skills, analytical abilities, and innovative thinking to transform creative ideas into functional solutions at scale.

Location: Must be based in Manchester, United Kingdom or London, United Kingdom

Company

hirify.global is a global, product-focused AI team revolutionizing business travel with cutting-edge technology and desirable products.

What you will do

• Utilize AI techniques including machine learning, deep learning, and generative AI to develop and implement solutions for real-world problems.
• Apply strong coding skills and analytical abilities to transform creative ideas into functional solutions.
• Employ statistical and data science methods for data-driven decisions and manipulating large datasets.
• Structure work and produce analyses, ML models, and Compound AI systems to answer complex business questions.
• Communicate complex data science topics in a clean and simple way to multiple partners and senior leadership.
• Collaborate with a global team across different continents to achieve project goals.

Requirements

• 6+ years of experience with a bachelor’s degree or 3+ years with a master’s degree.
• Proven ability to conceptualize business problems and solve them through data science solutions.
• Proven knowledge of AI techniques such as Bayesian methods, Clustering, Ensemble tree models, and NLP, with an excellent grasp of statistical concepts.
• Good understanding of LLMs, guardrails, RAG, and agentic AI.
• Strong passion for solving problems and finding patterns and insights within structured and unstructured data.
• Strong knowledge of hands-on practice in Python, with familiarity with popular machine learning libraries and frameworks such as scikit-learn, Hugging Face, PyTorch, and TensorFlow.
• Familiarity with MLOps concepts and comfortable with data cleansing using SQL and PySpark.
• Good written and oral communication skills, including the ability to communicate across business areas.

Nice to have

• Experience with MLFlow, AWS SageMaker, and Bedrock.
• Experience with feature stores, machine learning models as service, and monitoring dashboards.
• Some infrastructure knowledge (AWS, Kubernetes) and cost-awareness.

Culture & Benefits

• Flexible benefits tailored to each country, including health, welfare, retirement programs, and parental leave.
• Travel perks with deals each week from major travel providers.
• Access to over 20,000 courses for skill development.
• Opportunity to connect with colleagues through global Inclusion Groups.
• Commitment to providing equal consideration for employment and reasonable accommodation for disabilities.