At a Glance
- Tasks: Build innovative machine learning solutions and collaborate with diverse teams.
- Company: Join a dynamic team at a leading professional and financial services firm.
- Benefits: Enjoy competitive pay, flexible work options, and opportunities for growth.
- Other info: Be part of a diverse team driven by intellectual curiosity and collaboration.
- Why this job: Make a real impact using cutting-edge ML techniques in exciting projects.
- Qualifications: Experience in machine learning, Python, and cloud technologies required.
The predicted salary is between 60000 - 80000 £ per year.
As a Machine Learning Engineer in our Professional and Financial Services business unit, you will work on project teams delivering bespoke machine learning solutions to our clients. You will be responsible for implementing data-driven approaches, contributing to the design of scalable software architectures, and ensuring best practices are followed throughout development. You will collaborate closely with our commercial team to help shape and deliver high-quality projects. In the early stages of client engagements, you will contribute to defining the technical scope, ensuring that proposed solutions are both feasible and aligned with business objectives. Your work will play a critical role in ensuring we deliver impactful software within agreed timeframes. This role offers the opportunity to apply cutting-edge machine learning techniques to complex challenges in professional and financial services, while working alongside colleagues from diverse technical and commercial backgrounds.
What You'll Be Doing
- Building software and infrastructure that leverages Machine Learning
- Creating reusable, scalable tools to enable better delivery of ML systems
- Working with our customers to help understand their needs
- Working with data scientists and engineers to develop best practices and new technologies
- Implementing and developing Faculty's view on what it means to operationalise ML software
- Working in cross-functional teams of engineers, data scientists, designers and managers to deliver technically sophisticated, high-impact systems
- Working with senior engineers to scope projects and design systems
- Providing technical expertise to our customers
Who We're Looking For
- Understanding of, and experience with the full machine learning lifecycle
- Working with Data Scientists to deploy trained machine learning models into production environments
- Working with a range of models developed using common frameworks such as Scikit-learn, TensorFlow, or PyTorch
- Experience with software engineering best practices and developing applications in Python
- Technical experience of cloud architecture, security, deployment, and open-source tools ideally with one of the 3 major cloud providers (AWS, GCP or Azure)
- Demonstrable experience with containers and specifically Docker and Kubernetes
- An understanding of the core concepts of probability and statistics and familiarity with common supervised and unsupervised learning techniques
- Demonstrable experience of managing/mentoring more junior members of the team
- Outstanding verbal and written communication
- Excitement about working in a dynamic role with the autonomy and freedom you need to take ownership of problems and see them through to execution
What we can offer you:
The Faculty team is diverse and distinctive, and we all come from different personal, professional and organisational backgrounds. We all have one thing in common: we are driven by a deep intellectual curiosity that powers us forward each day. Faculty is the professional challenge of a lifetime. You'll be surrounded by an impressive group of brilliant minds working to achieve our collective goals. Our consultants, product developers, business development specialists, operations professionals and more all bring something unique to Faculty, and you'll learn something new from everyone you meet.
Machine Learning Engineer - Professional and Financial Services in London employer: Job Search Place Limited
At Faculty, we pride ourselves on being an exceptional employer, offering a vibrant work culture that fosters collaboration and innovation. As a Machine Learning Engineer, you'll have the opportunity to work with a diverse team of experts, engage in meaningful projects that leverage cutting-edge technology, and benefit from continuous professional development. Our commitment to intellectual curiosity and excellence ensures that you will thrive in an environment that values your contributions and supports your growth.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer - Professional and Financial Services in London
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We think you need these skills to ace Machine Learning Engineer - Professional and Financial Services in London
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!
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Craft a Tailored Cover Letter:For a full-time role at Job Search Place Limited, 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 Job Search Place Limited. 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 Job Search Place Limited
✨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!
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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
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✨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.
