At a Glance
- Tasks: Design and deploy scalable AI/ML solutions in a dynamic enterprise environment.
- Company: Join Airswift, a global leader in workforce solutions for energy and infrastructure.
- Benefits: Competitive pay, flexible work options, and opportunities for professional growth.
- Other info: Collaborative culture with a focus on continuous learning and innovation.
- Why this job: Make an impact with cutting-edge AI technologies and innovative projects.
- Qualifications: 10+ years in software development and machine learning; strong programming skills required.
The predicted salary is between 70000 - 90000 £ per year.
Duration: 5 months renewable
Location: London
Start date: ASAP
Payrate: £700.00 Inside IR35
The Senior AI/ML Research Engineer is an opportunity to join a Data & AI team focused on building production‑grade machine learning solutions across multiple business areas in a large‑scale enterprise environment.
Role Context
This position sits within a Data & AI organisation delivering scalable AI/ML solutions, with a strong focus on enterprise quality, reliability, and scalability. The Senior AI/ML Research Engineer will contribute to the development of modern machine learning systems in an environment where cloud‑based development, data platforms, and advanced AI tooling are central to delivery.
About the Role
The Senior AI/ML Research Engineer will design, develop, and deploy scalable AI/ML solutions from experimentation through to production. This role is central to building reusable machine learning architectures, supporting automation across the AI/ML lifecycle, and helping translate business needs into technical solutions.
Key Responsibilities
- Design and deploy large‑scale machine learning systems into production using modern engineering practices and tools.
- Build and maintain core ML infrastructure, including pipelines for feature engineering, model training, evaluation, deployment, and monitoring.
- Automate the full AI/ML lifecycle, covering data ingestion, experimentation, tuning, and visualisation.
- Collaborate with product teams to convert business requirements into scalable, reusable ML solutions.
- Partner with DevOps and infrastructure teams to improve deployment velocity, CI/CD processes, and reliability of data pipelines.
- Contribute to innovation by staying up to date with emerging AI/ML technologies and best practices.
- Support knowledge sharing and community initiatives across the organisation.
Required Experience & Qualifications
- Bachelor’s, Master’s, or PhD in a relevant discipline (Engineering, Computer Science, Statistics, or related fields).
- 10+ years of experience in software development and machine learning engineering.
- Strong expertise in designing large‑scale machine learning systems and architectures.
- Advanced programming skills (Python preferred) with experience in frameworks and tools such as JavaScript, Kafka, and reactive systems.
- Extensive experience with cloud‑based development, particularly on Azure, including AI/ML services and data platforms.
- Proven experience with Kubernetes for application deployment, scaling, and monitoring.
- Strong background in CI/CD pipeline design, automation, and maintenance.
- Hands‑on experience with data engineering tools and storage solutions (e.g., ADLS, Spark, Databricks, SQL/NoSQL databases).
- Experience with distributed computing and big data processing frameworks such as PySpark.
- Knowledge of infrastructure‑as‑code tools such as Terraform and Helm.
- Experience building and deploying GenAI solutions using frameworks such as LangChain and Azure OpenAI.
- Development of enterprise‑grade RAG (Retrieval‑Augmented Generation) systems, including context engineering and multimodal data pipelines.
- Design and deployment of autonomous multi‑agent systems using modern orchestration frameworks and evaluation approaches.
- Experience delivering Text‑to‑SQL solutions and natural language interfaces for structured data environments.
- Strong understanding of data processing, cleansing, and handling large structured and unstructured datasets.
- Solid foundation in Linux, scripting (Bash/PowerShell), and networking fundamentals.
- Excellent communication skills with the ability to translate complex technical concepts into business terms.
- Experience working in agile, cross‑functional, and globally distributed teams.
- Continuous learning mindset with a focus on emerging technologies and innovation.
About Airswift
Airswift is an international workforce solutions provider within the energy, process and infrastructure industries. Airswift partners with organisations worldwide to deliver critical talent across complex projects, offering global reach and industry expertise.
Artificial Intelligence / Machine Learning Engineer in London employer: Airswift
Airswift is an exceptional employer, offering a dynamic work environment in London where innovation and collaboration thrive. As a Senior AI/ML Research Engineer, you will be part of a forward-thinking Data & AI team dedicated to developing cutting-edge machine learning solutions, with ample opportunities for professional growth and continuous learning. The company fosters a culture of knowledge sharing and supports employees in staying at the forefront of emerging technologies, making it an ideal place for those seeking meaningful and rewarding careers.
StudySmarter Expert Advice🤫
We think this is how you could land Artificial Intelligence / Machine Learning Engineer in London
✨Tap into Online Data Science Communities
Join online communities focused on data science like Kaggle, LinkedIn groups, or Reddit threads. These are goldmines for temporary gigs, as you can network with professionals and potentially hear about opportunities at companies like Airswift before they're even advertised!
✨Show Off Your Skills With Projects
Got some cool data science projects? Showcase them on platforms like GitHub or create a personal portfolio website. This visibility is crucial for landing temporary roles—let recruiters see your actual skills in action, which can set you apart from the crowd.
✨Check Out Specialist Job Boards
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If you're currently at uni or recently graduated, tap into your school's career services. They often have connections with companies looking for temporary data science interns or contract workers, and they might even host job fairs with employers like Airswift.
We think you need these skills to ace Artificial Intelligence / Machine Learning Engineer in London
Some tips for your application 🫡
Highlight Your Data Projects:When applying for a temporary data science role at Airswift, make sure to showcase any relevant projects you've worked on. Whether it's a personal project, an academic undertaking, or contributions to an open-source initiative, detailing these experiences can really set you apart and demonstrate your practical skills.
Emphasise Your Analytical Skills:In your CV and cover letter, focus on the specific analytical skills that are key to data science. Mention any experience with statistical tools, programming languages like Python or R, and data visualisation software. Don't forget to include any certifications that may bolster your expertise!
Show Your Flexibility:Since this is a temporary role, it's important to convey your adaptability and willingness to learn. In your cover letter to Airswift, emphasise how quickly you can get up to speed with new tools or projects. Highlight any previous experiences where you've had to adjust to new environments or challenges.
Craft a Unique Data-Driven Cover Letter:Instead of the usual generic cover letter, spice it up with some data! Maybe you’ve improved a process by 20% in a past role or cleaned a dataset with over a million entries. Use these stats to your advantage to grab Airswift’s attention and show the tangible impact of your work.
How to prepare for a job interview at Airswift
✨Showcase Your Analytical Skills
For a data science gig, it's crucial to demonstrate your analytical abilities. Be ready to discuss previous projects and the methodologies you used. Think about how you can quantify your impact—did your analysis improve efficiency or save costs? These are the stories that will stick with interviewers at Airswift.
✨Brush Up on Technical Skills
You might face technical questions on tools relevant to data science, like Python, R, or SQL. Prepare to solve a problem live—perhaps they'll ask you to write a simple query or code snippet. It’s cool to talk about them, but we need to show we can do it in practice, especially in a temporary role where quick results matter.
✨Highlight Your Adaptability
Since this is a temporary position, emphasise your ability to learn quickly and adapt to new tools or workflows. Share examples of how you've thrived in fast-paced environments before, and how you can hit the ground running at Airswift.
✨Prepare a Portfolio of Your Work
Bring your portfolio to the table—showcase projects where you've leveraged data science techniques to solve problems. Whether it’s a GitHub repository or a set of case studies, having tangible examples of your work will help you stand out and show what you bring to the team at Airswift.
