Senior Machine Learning Engineer (AI)

Location: London, United Kingdom. Hybrid working model with 3 days per week in the Shoreditch office. The role includes travel to customer sites in North America, Europe, Asia, and Oceania for an average of 3–4 weeks per quarter.

Company

hirify.global is an AI company building simulation software and physics-enabled machine learning solutions for industrial engineering and manufacturing.

What you will do

• Deploy machine learning models and engineering surrogates into customer production environments, including deep learning on CAE, CFD, and FEA data, forecasting, anomaly detection, optimization, and control.
• Design and lead the architecture of data and machine learning systems, including training and inference pipelines and APIs.
• Build robust, scalable solutions for cloud and on-premise environments using Python, PyTorch, Pandas, FastAPI, SciPy, Kubeflow, and related tools.
• Work with data scientists, simulation engineers, and customers to define engineering and physics problems and establish measurable outcomes.
• Communicate technical trade-offs to senior stakeholders, influence product direction, and scope new customer projects.
• Mentor engineers and data scientists while providing technical direction across complex workstreams.

Requirements

• At least 3 years of industry experience after a Master’s degree or PhD in a commercial, non-research environment.
• Experience shipping machine learning systems end-to-end and at scale.
• Experience building reliable ML data pipelines, training and inference systems, and production APIs.
• Ability to work with 3D point-cloud and mesh data for geometry-aware modelling.
• Strong problem-solving, technical leadership, stakeholder communication, and customer-facing skills.
• Ability to work in a hybrid model with 3 days per week in the Shoreditch office and travel to customer sites.

Culture & Benefits

• Opportunity to build AI-native engineering products for aerospace, automotive, semiconductors, materials, and energy industries.
• Flat structure with emphasis on technical influence, challenging assumptions, and collaborative decision-making.
• Hybrid working model with work-from-home days and a sustainable working pace.
• Equity options and a 10% employer pension contribution.
• 25 days of annual leave plus public holidays, private medical insurance, enhanced parental leave, and a nursery scheme.
• Learning and development support, employee assistance, Wellhub membership, free office lunches, and transport-related benefits.