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- Tasks: Transform complex business challenges into innovative AI solutions and prototypes.
- Company: Dynamic private equity firm focused on leveraging AI for strategic decisions.
- Benefits: Hybrid work model, competitive pay, and opportunities for professional growth.
- Why this job: Join a cutting-edge team and shape the future of AI in a real-world setting.
- Qualifications: Strong Python and ML engineering skills, with a passion for AI technologies.
- Other info: Collaborative environment with a focus on learning and innovation.
The predicted salary is between 36000 - 60000 £ per year.
One of our private equity clients in the UK is searching for a hands-on AI / ML Engineer to help bridge deep technical capability with business-facing problem solving. They are exploring new ways of unlocking value from decades of unstructured “dark data” and need someone to help shape what modern AI looks like inside their organisation. You will be playing a key role in turning vague, messy business problems into concrete AI pipelines and prototypes that will inform major strategic decisions.
Responsibilities
- Act as a hands-on AI / ML engineer embedded directly in the business problem space
- Take ambiguous business challenges and refine them into real, provable AI use-cases
- Prototype solutions quickly, demo them internally, gather feedback and iterate
- Work with huge volumes of unstructured documents and data across multiple legacy systems
- Use GenAI, LLMs and semantic modelling to extract meaning, entities and patterns
- Build end-to-end solutions — from extraction to model testing to productionisation
- Collaborate with business stakeholders, data engineers and external vendors/startups
- Help influence and define the AI roadmap and tooling choices going forward
Qualifications
- Strong Python skills and real-world ML engineering experience
- Strong experience with modern GenAI / LLM frameworks: LangChain, LangGraph, PyTorch, etc.
- Comfort working with unstructured data: entity extraction, semantic search, vectorisation, RAG-like patterns
- Awareness of data engineering: pipelines, legacy data extraction, interfacing with data teams
- Experience or strong curiosity working with Azure and Azure Databricks
- A proactive stakeholder mindset - you enjoy teasing out real needs rather than waiting for specs
- A learner’s mindset - you keep up with the pace of AI and explore new tooling constantly
Location: Hybrid: 2–3 days onsite in Marble Arch. Duration: 6 months. Seniority Level: Mid-Senior level. Employment Type: Contract. Job Function: Information Technology.
AI / ML Engineer – Outside IR35 – Hybrid (2–3 days in Marble Arch) – 6 Months employer: Orbis Group
Contact Detail:
Orbis Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI / ML Engineer – Outside IR35 – Hybrid (2–3 days in Marble Arch) – 6 Months
✨Tip Number 1
Network like a pro! Reach out to your connections in the AI/ML space and let them know you're on the hunt for opportunities. You never know who might have a lead or can refer you directly to hiring managers.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI/ML projects, especially those that involve unstructured data. This will give potential employers a taste of what you can do and how you tackle real-world problems.
✨Tip Number 3
Prepare for interviews by brushing up on your Python and ML frameworks. Be ready to discuss your experience with GenAI and LLMs, and think of examples where you've turned vague business challenges into solid AI solutions.
✨Tip Number 4
Don't forget to apply through our website! We make it easy for you to find roles that match your skills and interests. Plus, it shows you're serious about joining our team and helps us keep track of your application.
We think you need these skills to ace AI / ML Engineer – Outside IR35 – Hybrid (2–3 days in Marble Arch) – 6 Months
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the job description. Highlight your Python skills and experience with GenAI frameworks like LangChain and PyTorch. We want to see how your background aligns with the role!
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're the perfect fit for this AI/ML Engineer position. Share specific examples of how you've tackled ambiguous business challenges and turned them into successful AI solutions.
Showcase Your Projects: If you've worked on any relevant projects, especially those involving unstructured data or AI pipelines, make sure to include them. We love seeing real-world applications of your skills, so don’t hold back!
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep everything organised and ensures your application gets the attention it deserves!
How to prepare for a job interview at Orbis Group
✨Know Your Tech Inside Out
Make sure you brush up on your Python skills and get familiar with the latest GenAI and LLM frameworks like LangChain and PyTorch. Be ready to discuss how you've used these technologies in real-world scenarios, as this will show your hands-on experience.
✨Understand the Business Context
Since the role involves turning vague business problems into concrete AI solutions, do some homework on the company’s industry and challenges. Think about how AI can unlock value from unstructured data and be prepared to share your ideas during the interview.
✨Showcase Your Prototyping Skills
Be ready to talk about your experience with prototyping AI solutions. Share examples of how you've quickly developed demos, gathered feedback, and iterated on your work. This will demonstrate your ability to work in a fast-paced environment and adapt to stakeholder needs.
✨Ask Insightful Questions
Prepare thoughtful questions that show your curiosity and proactive mindset. Inquire about their current AI roadmap, the types of unstructured data they deal with, and how they envision the role of an AI/ML engineer in shaping their strategy. This will highlight your engagement and interest in the position.