At a Glance
- Tasks: Design and optimise AI systems while collaborating with stakeholders to build innovative products.
- Company: Join a forward-thinking tech company focused on AI advancements.
- Benefits: Competitive salary, remote work options, and opportunities for professional growth.
- Other info: Dynamic team environment with a focus on continuous learning and innovation.
- Why this job: Be at the forefront of AI technology and make a real impact in product development.
- Qualifications: Bachelor's degree in a related field and 3+ years in AI product development.
The predicted salary is between 70000 - 90000 £ per year.
Job Title
AI Engineer II
Department
Data Science
Reports to
- SVP, Data Science
- £55,000
- Job Overview
The AI Engineer II is a mid-level position responsible for engineering AI based products and maintenance.
As a mid-level engineer in this role, you will work closely with senior engineers and non-technical business stake holders, contributing to the entire lifecycle of building and maintaining emerging LLM-based products.
An important aspect of this role would be product design and execution bearing cost efficiency and speed.
The ideal candidate would have skills in software programming, building agentic systems, mathematics, and Dev Ops (including container operations, CI/CD, and cloud engineering).
Good communication skills with an ability to demystify LLMs and agentic systems is a must, as stakeholders in AI products include software engineering teams as well as non-technical business partners.
Responsibility
- Design, develop, and optimise agentic AI systems.
- Work with Product/business stakeholders to capture and establish requirements for AI products.
- Steer consolidation of dataset requirements, acquiring data, management, and version control for AI applications.
- Monitor AI products in production, setting metrics to identify performance (accuracy / retrieval rates / hit rates), and establish corrective measures for restoring performance.
- Identify and implement appropriate tools for monitoring AI product performance in production.
- Ownership of technical documentation related to design, model selection, experiments, and production infrastructure.
- Continual learning and self-improvement with a focus on latest trends, techniques, and best practices in AI.
Qualifications & Skills
Need to have.
- Bachelor's degree in computer science, Engineering, or a related field.
- 3+ years of experience in AI product development or Machine Learning
- Proficient in Python.
- Built and deployed at least two LLM-based or NLP-heavy product in a real setting likely using agentic frameworks like Lang Graph, Lang Chain, Auto Gen etc.
- Strong mathematical, analytical, and problem-solving skills.
- Experience with retrieval systems, embeddings, and vector DBs like Weaviate or Pinecone.
- Ability to structure and execute an Agentic AI project from start to completion.
- Excellent communication and teamwork skills; ability to work in a team.
- Experience with cloud computing platforms like AWS.
- Familiarity with containerization and orchestration tools like Docker and Kubernetes.
- Experience with version control systems like Git.
- Ability to leverage coding agents for accelerated software development
Nice to have.
- Masters in a specific field such as Statistics, Data Science, Machine Learning, or AI.
- Knowledge of SQL and No SQL databases including construction of queries, query optimisation, and schema design.
- API development using standard tools such as Fast API or Flask.
- Good understanding of Machine Learning algorithms and models (Language processing models such as GPT, BERT, etc).
AI Engineer II in Glasgow employer: HW Management
As an AI Engineer II at our innovative company, you will thrive in a dynamic work culture that prioritises collaboration and continuous learning. We offer competitive salaries, comprehensive benefits, and ample opportunities for professional growth, all within a vibrant location that fosters creativity and technological advancement. Join us to be part of a forward-thinking team dedicated to pushing the boundaries of AI technology while enjoying a supportive environment that values your contributions.
StudySmarter Expert Advice🤫
We think this is how you could land AI Engineer II in Glasgow
✨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 HW Management!
✨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 AI Engineer II at HW Management.
✨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 HW Management.
✨Apply Directly through Our Website
When you find a suitable opening like AI Engineer II at HW Management, 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 AI Engineer II in Glasgow
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 HW Management, 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 HW Management. 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 HW Management
✨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 HW Management!
✨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.
