Machine Learning & AI Developer

Benefits

Parental leave

Not verified

Non-birth-parent leave

Not verified

Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

Not verified

Relocation assistance

Not verified

Childcare support

Not verified

Learning budget

Not verified

Verification

Not verified checked Jun 13, 2026

Salary

Not verified

401(k) match

Reported from DOL Form 5500 industry filing (not employer-specific)

Was this benefit information wrong? Tell us.

Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Mid From the posting source checked Jun 20, 2026

Schedule

Shift type

Not verified

Weekend work

Not verified

Company

Equity

Offered Verified - SEC 10-K source checked Jun 20, 2026

Application

Cover letter

Not verified

Assessment

Not verified

Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Machine Learning & AI Developer Prague, Czech Republic We are seeking a Machine Learning & AI Developer to design, build, and deploy data‑driven and AI solutions that enhance catastrophe modelling, with an emphasis on flood hazard and risk. You will work with hazard and vulnerability modellers, software engineers, and other experts to prototype and industrialise novel approaches that improve the accuracy, scalability, and resolution of Impact Forecasting's models. While the primary focus is flood, you will also support cross‑peril initiatives (e.g., wildfire, terrorism) and internal AI tools that accelerate research and development. A key initial responsibility will be contributing to an ML/AI‑based flood map quality assessment pipeline for new global flood models, replacing a manual QA process. What the day will look like Develop and implement ML/AI solutions to improve catastrophe models, focusing on flood hazard and risk. Build global flood risk quality classification models using geospatial, hydrological, and exposure datasets. Contribute to the design, development, and maintenance of the Impact Forecasting Knowledge Hub (AI chatbot), including data pipelines, model selection, and monitoring. Research and implement precipitation downscaling methods (e.g., CNNs, U‑Nets, diffusion, generative models) to improve spatial and temporal resolution of inputs. Design, run, and document proof‑of‑concept (PoC) studies, from problem framing to evaluation and recommendations. Skills and experience that will lead to success Proven experience (industry or advanced academic) in machine learning and/or applied AI, ideally on structured, time series, or geospatial data. Strong Python skills with common ML/AI and data science libraries (e.g., NumPy, pandas, scikit‑learn, PyTorch

Read the full description at english-careers-aon.icims.com. FewerJobs shows a preview and links to the original posting.