At a Glance
- Tasks: Design and build AI-powered software products while collaborating with diverse teams.
- Company: Join FemTechConf, a leader in connecting tech talent with innovative organisations.
- Benefits: Flexible work options, competitive pay, and opportunities for professional growth.
- Other info: Open to diverse backgrounds; your unique skills are valued here.
- Why this job: Be at the forefront of AI innovation and make a real impact in tech.
- Qualifications: Experience or interest in AI, machine learning, and software engineering.
The predicted salary is between 70000 - 90000 £ per year.
- AI Software Engineer Talent Network | London | Open Application
- Fem Tech Conf Partner Network
- Build the Next Generation of AI-Powered Products in London
Are you an AI Software Engineer, Machine Learning Engineer, Applied AI Engineer, Software Engineer, Backend Engineer, Data Engineer, LLM Engineer, AI Product Engineer, or Full-Stack Engineer with experience or interest in artificial intelligence?
Fem Tech Conf is building a network of exceptional AI and software engineering talent interested in connecting with our clients and partner organisations across the London and UK technology ecosystem.
By applying to this opportunity, your profile may be shared with selected Fem Tech Conf clients and partner organisations that are actively looking for engineers across areas such as:
- AI Software Engineering
- Machine Learning Engineering
- AI Product Development
- Automation
- AI Infrastructure
Our clients and partners include startups, scale‑ups, global technology companies, consulting organisations, enterprise technology teams, AI‑focused companies, research‑driven teams, and organisations investing in software, data, cloud, automation, and artificial intelligence.
This is an open application opportunity designed to connect strong AI and software engineering talent with current and future roles across our client and partner network.
What Our Clients Are Looking For
While requirements vary depending on the organisation, our clients are typically interested in AI software engineers with experience across one or more of the following areas:
- AI Software Engineering
- Building AI‑powered products, platforms, tools, or internal systems
- Integrating AI models into production software
- Developing intelligent features for web, mobile, Saa S, enterprise, or customer‑facing products
- Working with APIs, backend systems, data pipelines, and AI services
- Building scalable, reliable, and user‑focused AI applications
- Translating AI concepts into practical product features
- Machine Learning and Applied AI
- Machine learning model development, training, fine‑tuning, or evaluation
- Applied AI use cases across automation, prediction, classification, recommendation, search, or personalisation
- Python, Py Torch, Tensor Flow, scikit‑learn, Hugging Face, or similar tools
- Model evaluation, experimentation, and performance improvement
- ML pipelines, feature engineering, and model deployment
- Responsible and reliable AI implementation
- LLMs, Generative AI and AI Agents
- Large language models and generative AI applications
- Prompt engineering and AI workflow design
- Retrieval‑augmented generation, vector databases, embeddings, and semantic search
- AI agents, copilots, chatbots, automation tools, and intelligent assistants
- Evaluation, guardrails, monitoring, and reliability for LLM‑based systems
- Backend, Data and Cloud Engineering
- REST APIs, Graph QL, microservices, and distributed systems
- Databases such as Postgre SQL, Mongo DB, Redis, Snowflake, Big Query, or similar
- Data pipelines and analytics infrastructure
- AWS, Azure, Google Cloud, or similar cloud platforms
- Docker, Kubernetes, CI/CD, observability, and deployment workflows
- Product, Collaboration and Engineering Quality
- Working closely with product managers, designers, data scientists, researchers, and business teams
- Writing clean, scalable, maintainable, and well‑tested code
- Turning ambiguous problems into usable technical solutions
- Building prototypes, MVPs, and production‑ready features
- Code reviews, technical documentation, and engineering best practices
- User‑focused product thinking and strong communication skills
- Typical Responsibilities
- Depending on the client organisation and opportunity, responsibilities may include:
- Designing, building, testing, and maintaining AI‑powered software products, platforms, and internal tools
- Integrating machine learning models, LLMs, APIs, or AI services into production systems
- Developing backend, full‑stack, data, cloud, or AI infrastructure solutions
- Building AI agents, copilots, recommendation systems, automation tools, or intelligent product features
- Collaborating with product managers, designers, data scientists, researchers, and other engineers
- Supporting model evaluation, experimentation, deployment, and monitoring
- Improving the performance, reliability, scalability, and safety of AI‑enabled systems
- Building data pipelines, vector search systems, retrieval systems, or AI workflows
- Participating in code reviews, technical discussions, and agile development processes
- Contributing to architecture decisions for AI, data, backend, cloud, and platform systems
- Helping teams turn AI ideas into useful, reliable, and impactful products
- Ideal Candidate
We welcome applications from engineers with experience across AI software engineering, machine learning engineering, applied AI, backend engineering, data engineering, full‑stack engineering, cloud engineering, or product engineering.
Successful candidates may have
- Professional experience as an AI Software Engineer, Machine Learning Engineer, Applied AI Engineer, Software Engineer, Backend Engineer, Data Engineer, Full‑Stack Engineer, LLM Engineer, or similar role
- Experience building production software, AI applications, data systems, platforms, or APIs
- Understanding of AI, machine learning, LLMs, data pipelines, automation, or intelligent systems
- Experience with tools such as Py Torch, Tensor Flow, Hugging Face, Open AI, Lang Chain, vector databases, cloud platforms, or similar technologies
- Ability to write clean, scalable, and maintainable code
- Experience working in agile product or engineering teams
- Strong communication skills and the ability to work with technical and non‑technical stakeholders
- Interest in London‑based, UK‑based, hybrid, or remote AI and software engineering opportunities
- Passion for artificial intelligence, product development, innovation, and continuous learning
You do not need to have every skill listed. We encourage applications from candidates with different technical backgrounds, career paths, and levels of experience.
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StudySmarter Expert Advice🤫
We think this is how you could land AI Software Engineer Intern – London (ML/AI Focus)
✨Join Developer Communities!
Dive into online communities like GitHub or Stack Overflow. Contributing to open-source projects can really showcase your coding skills and catch the eye of hiring managers at companies like FemTechConf.
✨Attend Tech Meetups and Hackathons
Get your name out there by attending local tech meetups and hackathons. It's a perfect way to network with industry professionals and fellow interns, while also demonstrating your coding prowess in a collaborative setting.
✨Leverage University Career Services
Don't forget about your university's career services! They often have partnerships with companies like FemTechConf, and can help you access exclusive internship listings and workshops tailored for aspiring interns like us.
✨Show Off Your Work
Create a portfolio showcasing your coding projects on a platform like GitHub Pages or personal website. When applying for internships, we should link this to provide tangible proof of our skills and creativity, making us stand out to FemTechConf!
We think you need these skills to ace AI Software Engineer Intern – London (ML/AI Focus)
Some tips for your application 🫡
Show Off Your Side Projects:If you've got any side projects or contributions to open source, make sure to highlight them in your CV. We want to see what you can create! Include links to your GitHub or any relevant platforms to give us a taste of your coding style and skills.
Tailor Your CV for Software Engineering:Make your CV pop by tailoring it specifically for software engineering. List relevant programming languages, frameworks, and tools you’ve worked with, and showcase any tech stacks you're familiar with. This will help us quickly see how you fit into the FemTechConf team!
Let Your Passion Shine in Your Cover Letter:In your cover letter, don't just list your skills—tell us why you're passionate about software engineering! We love to see candidates who are eager to learn and grow, so share what excites you about this field and how a role at FemTechConf can help you on your journey.
Demonstrate Your Learning Mindset:As this is an internship, focus on your willingness to learn and adapt! We’re keen to see examples of how you’ve tackled challenges or learnt new skills in the past. Bring that eagerness to your application, showing us that you're ready to dive into a real-world software environment at FemTechConf!
How to prepare for a job interview at FemTechConf
✨Showcase Your Coding Skills
Since you're aiming for a software engineering internship, be ready to code on the spot or discuss your past projects. Brush up on your problem-solving skills, and practise coding challenges on platforms like LeetCode or HackerRank. We want to see how you approach problems and apply your knowledge, so having a few coding examples up your sleeve will definitely help!
✨Bring Your Portfolio to Life
Prepare a portfolio that highlights your coding projects—don't just list them! Be ready to explain your thought process, the technologies used, and any challenges you faced. It’s not just about the final product; we want to hear how you made it happen, so this narrative will show your depth of understanding and passion for software development.
✨Get Familiar with Technical Questions
Expect some technical questions or scenarios in the interview that assess your understanding of algorithms, data structures, and software design. Practise explaining your coding decisions clearly—it's less about getting the right answer and more about demonstrating your thought process and reasoning skills, which are crucial for growth in an internship.
✨Highlight Your Willingness to Learn
As an intern, your enthusiasm and eagerness to learn are key! During the interview, emphasise your willingness to tackle new challenges and pick up new skills. Companies like FemTechConf are often looking for candidates who can grow with them, so remind us why you're excited about opportunities to learn and contribute in a team environment.
