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- Tasks: Develop and manage MLOps pipelines while collaborating with cross-functional teams.
- Company: Join a leading financial services organization specializing in asset and wealth management.
- Benefits: Enjoy a competitive salary, bonus, 25 days holiday, and private medical cover.
- Why this job: Be part of a high-performing team in an exciting industry with ample career development opportunities.
- Qualifications: MSc or PhD in relevant fields and experience deploying machine learning models in production.
- Other info: Hybrid working with up to 3 days travel to London required.
The predicted salary is between 56000 - 84000 £ per year.
Machine Learning Engineer | Python | FinTech | London Hybrid Working | £70,000-£90,000 + bonus + benefits
Method Resourcing are proud to be working exclusively with a financial services organisation who specialise in both asset and wealth management whose goal is to provide the customer with honest and reliable advice on their finances. This is an opportunity to join an established business who operate at the highest standard and work with some of the most exciting brands in finance.
The role: Under the guidance of the Data Science Lead, you will collaborate with business and technology teams across WME to deliver machine learning models and actionable insights. Your primary responsibilities will include developing and managing MLOps pipelines along with the related infrastructure.
You’ll need experience with:
- Proven experience in deploying machine learning models into production environments.
- Extensive experience collaborating within cross-functional teams on data products and partnering with business stakeholders to support departmental or multi-departmental data initiatives.
- Advanced qualifications (MSc or PhD) or equivalent professional experience in computer science, statistics, applied mathematics, data management, information systems, information science, machine learning, or related quantitative fields.
- Proficient in agile methodologies with the ability to apply DevOps and MLOps practices to enhance communication, integration, code reuse, and automation across an organisation.
- Financial services background would be desirable.
This is truly a fantastic opportunity for any ambitious engineer who’s looking to join a high performing team within an exciting financial services institution. My client can offer the following benefits:
- Discretionary Bonus
- 25 days holiday plus bank holidays
- Pension scheme – employer 8%
- Income protection plan 70% of your salary
- Life assurance x4 of salary
- Private medical cover for you and your family & dental insurance
- Regular training and career development plans through coaching/mentoring and access to a learning portal
- Annual season ticket loans
- Employee discounts across a wide range of products
- Volunteering day paid for
- Wellbeing benefits including gym membership, employee assistance programme, eye care etc
Working arrangements: This role requires up to 3 days per week travel to London. Their office is located in central London so please ensure that you understand the working pattern before you apply.
Please apply, and if you’re interested in finding out more, please get in contact with Tom Morris by email (see below)
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Machine Learning Engineer employer: Method Resourcing Solutions Ltd
Contact Detail:
Method Resourcing Solutions Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer
✨Tip Number 1
Familiarize yourself with the specific machine learning frameworks and tools that are popular in the FinTech industry. Being able to discuss your experience with these technologies during the interview will show that you're well-prepared and knowledgeable.
✨Tip Number 2
Highlight any previous experience you have working in cross-functional teams. Be ready to share examples of how you've collaborated with business stakeholders to deliver data-driven solutions, as this is a key aspect of the role.
✨Tip Number 3
Since the role involves MLOps, brush up on your knowledge of DevOps practices and how they apply to machine learning. Being able to articulate how you can enhance communication and automation within the team will set you apart.
✨Tip Number 4
Research the financial services organization and its values. Understanding their mission to provide honest and reliable financial advice will help you align your answers with their goals during the interview process.
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Highlight Relevant Experience: Make sure to emphasize your experience in deploying machine learning models into production environments. Use specific examples that showcase your collaboration with cross-functional teams and your contributions to data initiatives.
Showcase Technical Skills: Clearly outline your technical skills, especially in Python, MLOps, and agile methodologies. Mention any relevant qualifications such as an MSc or PhD, and be specific about the tools and technologies you have used.
Tailor Your Application: Customize your CV and cover letter to reflect the job description. Highlight your understanding of the financial services sector and how your background aligns with the company's goals and values.
Express Enthusiasm: Convey your passion for machine learning and the financial services industry in your application. Explain why you are excited about this opportunity and how you can contribute to the team's success.
How to prepare for a job interview at Method Resourcing Solutions Ltd
✨Showcase Your Technical Skills
Be prepared to discuss your experience with deploying machine learning models into production. Highlight specific projects where you've successfully implemented MLOps pipelines and the impact they had on the business.
✨Demonstrate Collaboration Experience
Since the role involves working with cross-functional teams, share examples of how you've collaborated with both technical and non-technical stakeholders. Emphasize your ability to bridge the gap between data science and business needs.
✨Understand Agile and DevOps Practices
Familiarize yourself with agile methodologies and be ready to discuss how you've applied DevOps and MLOps practices in your previous roles. This will show that you can enhance communication and integration within the team.
✨Research the Financial Services Sector
Having a background in financial services is desirable for this position. Take some time to understand the industry trends and challenges, and be prepared to discuss how your skills can contribute to the organization's goals.
