Free Mid-level ai engineer CV (2026)

Start with a concise summary that highlights your hands-on experience, core model types you have worked with, and the primary domains where you delivered value. Follow with sections for experience, projects, technical skills, education, and relevant certifications so reviewers can scan for fit quickly.

In the UK, consider including a brief note on your current work eligibility or right-to-work status. Prioritise items that show progression from research or prototyping to deployed systems, such as model performance improvements, reductions in production latency, or feature adoption metrics.

Quantify outcomes where possible and keep each bullet focused on the problem, your action, and the measurable result.

Your summary should be two to three lines that state your role, years of hands-on experience, and the value you bring to teams and products. Use plain language that mentions the models, frameworks, or product areas you work in so your summary aligns with job descriptions you are targeting.

For example, instead of a vague claim about being experienced in AI, write that you are an AI engineer with three years building and deploying computer vision models that reduced false positives by 22 per cent in a production pipeline. That format tells hiring teams what you do and the impact you produce.

List roles in reverse chronological order and include a short context line for the company and product you supported, followed by 3 to 6 achievement bullets. Each bullet should be a single sentence that begins with an action verb, describes the technical work, and ends with a measurable outcome or concrete effect on the product.

Example bullets you can adapt are, Built and deployed an object detection pipeline using PyTorch and ONNX, improving inference throughput by 2x and reducing average latency from 180 ms to 90 ms, and Implemented data augmentation and curriculum learning that increased validation F1 by eight percentage points on a noisy dataset.

Select two to four projects that demonstrate end-to-end ownership, from data collection and preparation through model deployment and monitoring. Emphasise outcomes for stakeholders, include links to your repository or portfolio if permissible under your current employer's policy, and tailor each project to the target role.

When applying to NHS or healthcare‑adjacent teams, reference the impact for patient outcomes, efficiency, or safety where appropriate.

In the United Kingdom, CVs are typically concise and scannable, often two pages for mid‑level roles. Use a clean layout with clear section headings, bullet points, and consistent typography.

Include contact details (name, UK address, phone, and a professional email).

If you are applying to NHS roles, be mindful of pay bands and any required disclosures. Mention your right-to-work status and, if applicable, your National Insurance number in a secure format only when asked.

Date format should be DD/MM/YYYY.

Education should reference the UK system (GCSEs, A-levels, UCAS, and degrees from recognised universities, including Russell Group institutions). Use UK spelling and idioms throughout.

When listing salaries, present ranges in £ and indicate whether you expect to be paid within a band or role level. Reference UK job boards such as Reed, Indeed UK, Totaljobs, and LinkedIn, and mention your eligibility to work in the UK.