At a Glance
- Tasks: Build and deploy innovative GenAI applications using cutting-edge technologies.
- Company: Join a forward-thinking tech company focused on AI solutions.
- Benefits: Enjoy competitive pay, flexible work options, and opportunities for growth.
- Other info: Collaborative environment with exciting projects and career advancement.
- Why this job: Make a real impact in the AI field while developing your skills.
- Qualifications: Strong Python skills and experience in AI/ML engineering required.
The predicted salary is between 60000 - 80000 £ per year.
Seeking a GenAI Engineer with strong hands-on experience in building end-to-end AI applications. The role requires integrating data from multiple systems, extracting and parsing information from documents and images, interacting with structured databases, storing parsed content in a vector database, and implementing robust retrieval pipelines. The engineer must also ensure solution quality through evaluation frameworks, ground-truth validation, and defined performance metrics.
Key Responsibilities
- Design and build GenAI/RAG-based applications using data from multiple enterprise systems.
- Integrate with structured and unstructured data sources, including databases, APIs, files, and document repositories.
- Develop pipelines to parse and extract data from documents and images using OCR, document intelligence, and related tools.
- Process and structure extracted content for downstream AI use cases.
- Store parsed and chunked content in a vector database and manage embeddings effectively.
- Implement and optimize retrieval pipelines, including chunking, indexing, metadata tagging, filtering, and reranking.
- Build workflows to interact with relational and enterprise databases for querying and enrichment.
- Ensure the application follows strong evaluation practices, including accuracy, groundedness, relevance, hallucination checks, and response quality against ground truth.
- Work closely with architects, platform teams, and business stakeholders to deliver scalable and secure solutions.
- Follow enterprise standards for security, governance, observability, and performance.
Required Skills and Experience
- Strong experience in AI/ML engineering, with hands-on exposure to Generative AI use cases.
- Experience in building RAG applications in enterprise environments.
- Strong knowledge of document parsing, OCR, and image-based data extraction.
- Experience with LLM orchestration frameworks and prompt design.
- Experience with vector databases and semantic search.
- Very Strong programming skills in Python.
- Experience working with SQL/NoSQL databases and enterprise data integration patterns.
- Understanding of evaluation frameworks for GenAI systems using benchmark datasets and ground-truth-based validation.
- Experience in building scalable APIs/services and production-grade AI workflows.
Preferred Skills
- Experience with Azure-based AI stack.
- Experience with high-volume document processing.
- Familiarity with enterprise architecture, security, and compliance controls.
- Exposure to monitoring, model evaluation, and AI observability tools.
Preferred Profile
- Able to independently build and deploy GenAI applications from ingestion to retrieval and evaluation.
- Strong problem-solving skills with a practical implementation mindset.
- Comfortable working across data engineering, AI engineering, and application integration.
StudySmarter Expert Advice🤫
We think this is how you could land GenAI Python Engineer/Hybrid in Sheffield
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like iBSC!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like GenAI Python Engineer/Hybrid at iBSC.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like iBSC.
✨Apply Directly through Our Website
When you find a suitable opening like GenAI Python Engineer/Hybrid at iBSC, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace GenAI Python Engineer/Hybrid in Sheffield
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at iBSC, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at iBSC. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at iBSC
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at iBSC!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
