At a Glance
- Tasks: Build and launch AI/ML applications that drive real business results.
- Company: Rapidly scaling enterprise with a focus on innovation and impact.
- Benefits: Competitive daily rate, performance bonus, and comprehensive benefits package.
- Other info: Enjoy high autonomy and work in an agile team focused on speed and results.
- Why this job: Make a tangible impact by deploying cutting-edge AI technologies in a dynamic environment.
- Qualifications: Experience in ML/AI software, Python, and cloud platforms like AWS or Azure.
The predicted salary is between 50000 - 60000 £ per year.
A rapidly scaling enterprise is looking for a delivery-focused engineer to turn machine learning concepts into functional, revenue-driving products. This is a practical deployment role rather than an academic research position; the focus is entirely on shipping robust models that solve concrete operational challenges. You will bridge the gap between data architecture, cloud infrastructure, and predictive modelling.
Core Responsibilities
- Architect, train, and launch production-grade artificial intelligence and machine learning applications.
- Own the end-to-end development cycle, from raw data ingestion to model deployment and runtime optimisation.
- Adapt, fine-tune, and embed Large Language Models (LLMs) directly into corporate operational workflows.
- Partner with infrastructure and data engineering squads to scale and produce machine learning codes.
- Construct resilient data pipelines and secure APIs to feed downstream AI services.
- Advise on high-level architecture across both machine learning stacks and cloud systems.
Required Technical Background
- Demonstrated track record of shipping and maintaining live ML/AI software in commercial environments.
- Advanced proficiency in Python alongside deep learning ecosystems like PyTorch or TensorFlow.
- Hands-on engineering experience within major cloud platforms (AWS, Azure, or GCP).
- Deep understanding of core data engineering methodologies and automated pipeline design.
- Practical experience leveraging Generative AI technologies, including Retrieval-Augmented Generation (RAG), prompt optimization, and model fine-tuning.
- Thrives in high-velocity, output-oriented engineering cultures.
Preferred Extras
- Familiarity with MLOps frameworks, including continuous integration/deployment (CI/CD) for models, version control, and drift monitoring.
- Working knowledge of embeddings and vector storage solutions.
- Background in developing micro services and back-end API architectures.
- Prior experience in external consulting or stakeholder-facing engineering roles.
What Makes This Unique
- Tangible Output: Focus on building applications that go live, avoiding dead-end R&D loops.
- High Autonomy: Direct influence over how advanced computing technologies are adopted across an expanding organisation.
- Execution Culture: Work alongside an agile team structured entirely around speed-to-market and measurable impact.
SC Cleared AI / ML Engineer employer: IO Associates
As a rapidly scaling enterprise, we pride ourselves on fostering a dynamic work culture that prioritises innovation and tangible results. Our fully remote or hybrid working options provide flexibility, while our commitment to employee growth through hands-on experience with cutting-edge AI technologies ensures that you will thrive in a high-velocity environment. Join us to make a meaningful impact by turning machine learning concepts into functional products that drive revenue.
StudySmarter Expert Advice🤫
We think this is how you could land SC Cleared AI / ML Engineer
✨Tip Number 1
Network like a pro! Reach out to your connections in the AI/ML field and let them know you're on the lookout for opportunities. You never know who might have the inside scoop on a role that’s perfect for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your past projects, especially those involving machine learning applications. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on common technical questions related to AI and ML. Practice explaining your thought process clearly, as communication is key in these roles.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got some fantastic opportunities waiting for you, and applying directly can sometimes give you an edge over other candidates.
We think you need these skills to ace SC Cleared AI / ML Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the role of SC Cleared AI / ML Engineer. Highlight your experience with machine learning applications and any relevant projects you've worked on. We want to see how your skills align with our needs!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and ML, and how you can contribute to our team. Keep it concise but impactful – we love a good story!
Showcase Your Technical Skills:Don’t forget to highlight your technical expertise in Python, cloud platforms, and deep learning frameworks. We’re looking for hands-on experience, so be specific about the tools and technologies you’ve used in your previous roles.
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at IO Associates
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technical skills listed in the job description. Brush up on your Python, PyTorch, and TensorFlow knowledge, and be ready to discuss your hands-on experience with cloud platforms like AWS or Azure. Prepare to share specific examples of how you've shipped ML/AI software in commercial settings.
✨Showcase Your Problem-Solving Skills
Since this role focuses on turning concepts into functional products, be prepared to discuss real-world challenges you've tackled using machine learning. Think about how you’ve architected, trained, and launched applications, and be ready to explain your thought process and the impact of your solutions.
✨Demonstrate Your Collaboration Skills
This position requires working closely with infrastructure and data engineering teams. Highlight your experience in cross-functional collaboration and how you’ve partnered with others to scale machine learning codes or construct resilient data pipelines. Share examples that showcase your ability to work in a team-oriented environment.
✨Be Ready for Practical Scenarios
Expect to face practical scenarios or case studies during the interview. Prepare to discuss how you would adapt and fine-tune Large Language Models or design automated pipelines. Practising these scenarios can help you articulate your approach clearly and confidently.
