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- Tasks: Lead the development of scalable AI/ML solutions and MLOps frameworks for a prestigious investment bank.
- Company: Join a top-tier investment bank focused on innovative AI/ML technologies in capital markets.
- Benefits: Enjoy remote work flexibility and a competitive day rate with potential contract extensions.
- Why this job: Be at the forefront of AI/ML innovation while collaborating with diverse teams in a dynamic environment.
- Qualifications: 2+ years in MLOps and 3+ years in AI/ML engineering, with strong Python and SQL skills.
- Other info: Work on a greenfield project that shapes the future of AI/ML in investment banking.
The predicted salary is between 43200 - 72000 £ per year.
We are partnering with a prestigious investment bank to find a highly skilled and hands-on Machine Learning Operations (MLOps) Lead. This role will be pivotal in building out a greenfield framework for the deployment and management of scalable AI/ML solutions, specifically for the front and Middle Office user base.
The role is to define and set up a greenfield standardized MLOps framework for capital markets and set up all the tools and best practices to educate data scientists and equip them with the right tools and expertise. A strong understanding of DevOps, machine learning, and data engineering is required to enable the right candidate to implement the MLOps processes.
You will gain exposure to lots of different business areas and business stakeholders, so relationship building and good communication will be key. You will bring expertise in data science or data engineering, with a specific focus on MLOps for at least 2 years. This platform is critical and will be rolled out across the bank, so we are looking for only the highest calibre candidates with experience building and being responsible for greenfield MLOps pipelines that handle very large datasets.
You will be responsible for building out a greenfield standardized framework for capital markets. The core platform is built on Azure Databricks Lakehouse, consolidating data from various front and Middle Office systems to support BI, MI, and advanced AI/ML analytics.
As a lead, you will shape the MLOps framework and establish best practices for deploying and managing AI/ML solutions for a diverse and dynamic user base, including data scientists, quants, risk managers, traders, and other tech-savvy users.
- Lead the development of AI/ML CI/CD pipelines and frameworks for supporting AI/ML and Data Science solutions on Azure Databricks.
- Define and implement best practices for DataOps, DevOps, ModelOps, and LLMOps to standardize and accelerate the AI/ML life cycle.
- Collaborate with Data Scientists and teams across Front Office Quant teams, Sales/Trading desks to build, monitor, and maintain AI/ML solutions.
- Adopt cutting-edge advancements in GenAI and LLM technologies to keep the platform at the forefront of innovation.
- Align with the bank's central Enterprise Advanced Analytics & Artificial Intelligence group to ensure alignment with organizational goals, strategies, and governance.
- Manage large datasets and support data preparation, integration, and analytics across various data sources (orders, quotes, trades, risk, etc.).
Requirements:
- 2+ years of experience in MLOps and at least 3 years in AI/ML engineering.
- Proficiency with ML frameworks and libraries in Python.
- Expertise in Azure DevOps and GitHub Actions.
- Strong programming skills in Python and SQL; solid understanding of AI/ML algorithms, model training, evaluation (including hyperparameter tuning), deployment, monitoring, and governance.
- Experience in handling large datasets and performing data preparation and integration.
- Experience with Agile methodologies and SDLC practices.
Work on a greenfield project with a major global investment bank. Play a key role in building scalable AI/ML solutions across Capital Markets. Remote work flexibility with a competitive day rate.
If you are a talented MLOps professional with the expertise to help build and scale advanced AI/ML solutions in the investment banking space, we would love to hear from you.
Building Performance Consultant employer: CipherTek Recruitment
Contact Detail:
CipherTek Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Building Performance Consultant
✨Tip Number 1
Network with professionals in the investment banking and MLOps fields. Attend industry events, webinars, or meetups to connect with potential colleagues and learn about the latest trends and technologies. This can help you gain insights into what the bank is looking for and may even lead to referrals.
✨Tip Number 2
Familiarise yourself with Azure Databricks and its capabilities. Since the role involves building a framework on this platform, having hands-on experience or completing relevant online courses can set you apart from other candidates. Demonstrating your knowledge of this specific technology will show your commitment and readiness for the role.
✨Tip Number 3
Prepare to discuss your previous experiences with greenfield MLOps projects. Be ready to share specific examples of how you've built and managed MLOps pipelines, particularly those that handle large datasets. This will showcase your practical skills and understanding of the challenges involved in such projects.
✨Tip Number 4
Brush up on your communication and relationship-building skills. Since the role requires collaboration with various stakeholders, being able to articulate complex technical concepts in a clear and engaging manner will be crucial. Practice explaining your past projects to non-technical audiences to enhance your ability to connect with diverse teams.
We think you need these skills to ace Building Performance Consultant
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in MLOps, AI/ML engineering, and any relevant projects you've worked on. Emphasise your proficiency with Azure Databricks, Python, and SQL, as well as your understanding of DevOps practices.
Craft a Compelling Cover Letter: In your cover letter, explain why you are passionate about building scalable AI/ML solutions in the investment banking sector. Mention specific experiences that demonstrate your ability to lead MLOps initiatives and collaborate with diverse teams.
Showcase Relevant Projects: If you have worked on greenfield projects or have experience with large datasets, be sure to include these examples in your application. Detail your role and the impact of your contributions to highlight your expertise.
Highlight Communication Skills: Since relationship building and communication are key for this role, provide examples of how you've successfully collaborated with stakeholders in previous positions. This will show that you can effectively engage with various business areas.
How to prepare for a job interview at CipherTek Recruitment
✨Showcase Your Technical Expertise
Be prepared to discuss your experience with MLOps, AI/ML engineering, and the specific tools you've used, such as Azure Databricks and Python. Highlight any projects where you've built scalable solutions or managed large datasets.
✨Demonstrate Communication Skills
Since relationship building is key in this role, practice explaining complex technical concepts in simple terms. Be ready to share examples of how you've collaborated with diverse teams, including data scientists and traders.
✨Understand the Business Context
Research the investment banking sector and understand how MLOps can impact capital markets. Being able to relate your technical skills to business outcomes will show that you’re not just a techie but also understand the bigger picture.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving abilities in real-world scenarios. Think about challenges you've faced in previous roles and how you overcame them, particularly in relation to deploying and managing AI/ML solutions.
