At a Glance
- Tasks: Lead AI projects, develop production-grade systems, and mentor junior engineers.
- Company: Join a Big 4 professional services firm at the forefront of innovation.
- Benefits: Competitive salary, flexible working, and a chance to grow in a tech-driven environment.
- Other info: Exciting career growth opportunities in a dynamic, hybrid work environment.
- Why this job: Make an impact in AI and technology while collaborating with top professionals.
- Qualifications: Strong Python skills, backend development experience, and knowledge of AI tools required.
The predicted salary is between 70000 - 70000 £ per year.
Salary: £70,000 - 70,000 per year
Requirements
- Significant senior backend development experience with strong Python proficiency, including async programming, concurrency, and multithreading.
- Expertise in RESTful API design, OpenAPI/Swagger documentation, and API lifecycle best practices.
- Hands-on experience with ML libraries including PyTorch, PySpark, scikit-learn, and Hugging Face Transformers.
- Proficiency with AI tooling such as Azure ML, Databricks, MLflow, LangChain, and LangGraph.
- Proven experience with Git, unit testing, containerisation, and agile methodologies, including Jira and Confluence.
- Good knowledge of generative AI, machine learning, deep learning, or NLP.
- Strong communication skills and the ability to explain technical concepts to varied audiences.
- Bachelor's degree in Computer Science, AI, Data Science, Statistics, Engineering, or a related technical field; a master's degree or PhD is preferred.
- Advanced certifications in AI, machine learning, cloud computing, or data engineering are highly advantageous.
- A professional accounting qualification is desirable but not required.
- Experience with Microsoft Graph API is welcomed.
- Background in audit, financial services, or regulated industry technology is welcomed.
Responsibilities
- Lead hands-on technical delivery of AI projects and contribute actively to codebases and architectural decisions.
- Develop and deploy production-grade AI systems using Azure, Databricks, and generative AI tooling.
- Own the implementation of ML pipelines, APIs, and data integration workflows.
- Enforce MLOps best practices, coding standards, version control, and performance optimisation.
- Collaborate cross-functionally with data scientists, product managers, platform engineers, QA, and audit professionals.
- Mentor junior engineers and contribute to internal capability-building and knowledge-sharing initiatives.
Technologies
- AI
- API
- Azure
- Backend
- Cloud
- Confluence
- Databricks
- Git
- JIRA
- Machine Learning
- Network
- OpenAPI
- PyTorch
- Python
- PySpark
- Swagger
We are a Big 4 professional services firm with an Audit Technology team that is at the forefront of innovation, combining artificial intelligence, data engineering, analytics, and software development to transform how audit is delivered. Backed by a global network and significant investment in technology capability, our team has experienced rapid growth and is building exciting products at scale. This is a permanent, full-time hybrid role based in London, Manchester, Leeds, or Glasgow, with flexible working available across multiple UK locations. We offer a competitive salary and benefits package, and the chance to join a rapidly growing technology capability within one of the world's leading professional services firms.
Manager - Lead AI Engineer employer: Sivara GmbH
As a leading Big 4 professional services firm, we offer an exceptional work environment that fosters innovation and collaboration. Our Audit Technology team is at the cutting edge of AI and data engineering, providing employees with unique opportunities for growth and development in a dynamic hybrid setting across major UK cities. With a competitive salary, comprehensive benefits, and a commitment to mentoring, we empower our team members to excel in their careers while contributing to transformative projects.
StudySmarter Expert Advice🤫
We think this is how you could land Manager - Lead AI Engineer
✨Get Involved in Data Science Meetups
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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 Sivara GmbH.
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We think you need these skills to ace Manager - Lead AI Engineer
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 Sivara GmbH, 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 Sivara GmbH. 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 Sivara GmbH
✨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 Sivara GmbH!
✨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.
