At a Glance
- Tasks: Lead the development of cutting-edge AI and machine learning solutions to drive innovation.
- Company: Join Fitch Group, a leader in emerging technology with a collaborative culture.
- Benefits: Enjoy a great work-life balance, competitive salary, and opportunities for professional growth.
- Other info: Work in a dynamic environment with excellent career advancement opportunities.
- Why this job: Make a real impact in the exciting field of AI and machine learning.
- Qualifications: 5+ years of experience in ML/AI engineering and strong coding skills.
The predicted salary is between 80000 - 100000 £ per year.
The Fitch Group Emerging technology AI Center of excellence (COE) group is seeking a principal machine learning or AI engineer to be part of a team that will be dedicated to building and supporting Generative AI, Machine learning, Deep Learning and Data science solutions across the organization. The position will be based out of our London or Manchester office.
Specific Emerging Technology team objectives are:
- Gen AI/ML technology implementation with business and product owners
- Emerging Tech Governance function covering policies, guidelines and processes to govern AI/ML enabled components as well as third party AI governance
- Lead and support other enterprise-level AI exploration tools and capabilities
- Provide guidance and support for safe development and deployment of AI
What We Offer:
- This will be a high impact role with significant visibility where the candidate will work on some flagship Fitch products
- The candidate will have an excellent opportunity to work in the cutting-edge field of machine learning and data science
- Fitch promotes an excellent work culture and is known for providing a good work life balance
We’ll Count on You To:
- Work closely/as part of the product squads to build, integrate, and deploy GenAI, multi-AI-Agents and data science solutions.
- Ensure sharing best practices and learnings with other squad members.
- Design and spearhead the development of Gen AI, AI Agents and MLOps platforms, applications, and solutions driven by GenAI, deep learning and machine learning to address business challenges and elevate product performance.
- Build standards and recommendations for the AI engineering tech stack and data science models used across different enterprise AI use cases.
- Work closely with AI implementation, governance, and enterprise architecture squads to apply the appropriate standards.
- Keep abreast of the latest vendors across different areas of emerging technologies and actively participate in vendor evaluations and tool assessments for relevant use cases.
- Where appropriate, onboard the right solutions into the platform.
- Effectively communicate advanced data science/ML concepts in simple language to the business stakeholders always focusing on its applicability to Fitch business.
- Develop and deploy machine learning and gen AI solutions to meet enterprise goals and support experimentation and innovation.
- Collaborate with data scientists to identify innovative machine learning and Gen AI solutions that leverage data to meet business goals.
- Designs and develops scalable solutions and GenAI and ML workflows that leverage machine learning, gen AI and deep learning models to meet enterprise requirements.
- Actively participate in maintaining SLAs for Production applications and support.
- Create metrics to continuously evaluate the performance of machine learning solutions and improve the performance of existing machine learning solutions.
- Build with AWS and Azure cloud computing services providing the necessary infrastructure, resources, and interfaces to enable data loading and LLM workflows.
- Use Python/Java and large-scale data workflow orchestration platforms e.g. Airflow to construct software artifacts for ETL, interfacing with diverse data formats and storage technologies, and incorporate them into robust data workflows and dynamic systems.
What You Need to Have:
- Work experience as a ML or AI engineer (5+ years)
- Deep understanding of Agentic AI systems and multi-agent architectures
- Proficiency in machine learning and deep learning algorithms such as Deep learning, NLP, Neural networks, multi-class classifications, decision trees, support vector machines
- Strong adherence to software and ML development fundamentals (e.g. code quality considerations, automated testing, source version control, optimization)
- Prior experience working on building Gen AI frameworks and leveraging and/or finetuning LLM’s.
- Experience building/enhancing search and information retrieval systems
- Exposure/experience in containerization technologies like docker, Kubernetes, AWS EKS etc.
- Knowledge of popular Cloud computing vendor (AWS and Azure) infrastructure
Lead Machine Learning Engineer, Associate Director (Manchester) employer: Fitch Group
Fitch Group is an exceptional employer, offering a dynamic work environment in Manchester where innovation meets collaboration. Employees benefit from a strong work-life balance, opportunities for professional growth in cutting-edge AI and machine learning technologies, and the chance to contribute to impactful projects that shape the future of finance. With a culture that prioritises employee well-being and continuous learning, Fitch Group stands out as a rewarding place to advance your career.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Machine Learning Engineer, Associate Director (Manchester)
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at local meetups. We can’t stress enough how important it is to make connections; you never know who might have the inside scoop on job openings.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects. We all love a good visual, and having tangible examples of your work can really set you apart from the crowd.
✨Tip Number 3
Prepare for those interviews! Brush up on your technical knowledge and be ready to discuss your past projects in detail. We recommend practicing common interview questions with a friend or using mock interview platforms.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are genuinely interested in joining our team!
We think you need these skills to ace Lead Machine Learning Engineer, Associate Director (Manchester)
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Lead Machine Learning Engineer role. Highlight your experience with AI, ML, and any relevant projects you've worked on. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about machine learning and how you can contribute to our team. Keep it concise but impactful – we love a good story!
Showcase Your Projects:If you've worked on any cool AI or ML projects, make sure to mention them in your application. We’re keen to see your hands-on experience and how you’ve tackled real-world challenges using your skills.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re serious about joining the StudySmarter family!
How to prepare for a job interview at Fitch Group
✨Know Your Tech Inside Out
Make sure you’re well-versed in the latest machine learning and AI technologies, especially those mentioned in the job description. Brush up on your knowledge of GenAI, deep learning, and multi-agent architectures. Being able to discuss these topics confidently will show that you're not just familiar with the concepts but can also apply them effectively.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples where you've tackled complex problems using machine learning solutions. Think about challenges you've faced in previous roles and how you approached them. This will demonstrate your ability to think critically and innovate, which is crucial for a lead role.
✨Communicate Clearly and Effectively
Since you'll need to explain advanced data science concepts to business stakeholders, practice simplifying complex ideas into layman's terms. During the interview, focus on how your solutions can directly impact the business, making it relatable to non-technical audiences.
✨Be Ready for Technical Questions
Expect to dive deep into technical discussions, so brush up on your coding skills, particularly in Python and Java. You might be asked to solve problems on the spot or explain your thought process behind certain algorithms. Practising coding challenges beforehand can help you feel more prepared and confident.
