Machine Learning Engineer III (AI)

TL;DR

Machine Learning Engineer III (AI): Designing, building, and optimizing intelligent systems using various AI techniques for real-world problems. Focus on the full lifecycle from raw data to deployed models, including generative AI, LLMs, and agentic AI systems.

Location: Expected to work from Manchester, United Kingdom or London, United Kingdom. The team collaborates globally across different continents.

Company

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

What you will do

• Develop and implement AI solutions using machine learning, deep learning, generative AI, and statistical modeling for ranking, chatbots, intent recognition, agentic AI, recommender systems, computer vision, and NLQ.
• Apply strong coding, analytical abilities, and innovative thinking to transform creative ideas into functional solutions.
• Employ statistical and data science methods to make data-driven decisions and manipulate large datasets for business insights.
• Structure work, frame issues, and produce analyses/ML models/Compound AI systems that answer complex business questions pragmatically.
• Communicate complex data science topics simply to multiple partners and senior leadership.
• Collaborate with a global team across different continents to achieve project goals.

Requirements

• 8+ years of experience with a Bachelor’s degree or 5+ 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 and methods.
• Good understanding of LLMs, guardrails, RAG, and agentic AI.
• Strong passion for solving problems and finding patterns and insights within structured and unstructured data, with industry experience in leveraging AI techniques on real-world large datasets.
• 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.
• Comfortable with data cleansing using SQL and PySpark.

Nice to have

• Experience with MLFlow, AWS SageMaker, and Bedrock.
• Familiarity with MLOps concepts.
• 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 and welfare insurance plans, retirement programs, parental leave, adoption assistance, and wellbeing resources.
• Travel perks, offering weekly deals from major travel providers on flights, hotels, cruises, and car rentals.
• Opportunities to develop skills with access to over 20,000 courses on a learning platform, leadership courses, and internal job openings.
• An inclusive culture championing diversity, with global Inclusion Groups for connecting with colleagues.