At a Glance
- Tasks: Lead the development of AI/ML pipelines and frameworks for investment banking.
- Company: Join a prestigious investment bank focused on innovative AI/ML solutions.
- Benefits: Enjoy remote work flexibility and a competitive day rate up to £850.
- Why this job: Be part of a greenfield project shaping the future of capital markets with cutting-edge technology.
- Qualifications: 2+ years in MLOps and 3+ years in AI/ML engineering required.
- Other info: This is a 12-month contract role with potential extensions.
The predicted salary is between 120000 - 200000 £ 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. You MUST be hands-on. A strong understanding of DevOps, machine learning, and data engineering is required to enable the right candidate to implement the MLOps processes.
This team are a specialist team and this role in particular is a key position. Once the framework is established, you will become the gatekeeper to lots of other divisions within the bank, who will leverage your knowledge and expertise. As such, 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 standardised 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.
Core Responsibilities:- 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.).
- 2+ years of experience in MLOps and at least 3 years in AI/ML engineering.
- Knowledge in Azure Databricks and associated services.
- Proficiency with ML frameworks and libraries in Python.
- Proven experience deploying and maintaining LLM services and solutions.
- Expertise in Azure DevOps and GitHub Actions.
- Familiarity with Databricks CLI and Databricks Job Bundle.
- Strong programming skills in Python and SQL; familiarity with Scala is a plus.
- 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.
- Strong problem-solving, analytical, and communication skills.
- Work on a greenfield project with a major global investment bank.
- Gain deep expertise in MLOps, Azure Databricks, GenAI, and LLM technologies.
- 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. Apply now!
If you meet the qualifications and are excited about this opportunity, please submit your CV. We look forward to hearing from you!
Machine Learning Consultant employer: CipherTek Recruitment
Contact Detail:
CipherTek Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Consultant
✨Tip Number 1
Network with professionals in the investment banking and MLOps space. Attend industry meetups, webinars, or conferences 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 functionalities. Since this role heavily relies on this platform, consider taking online courses or tutorials that focus on building MLOps pipelines using Azure Databricks. Demonstrating your hands-on experience with this tool will set you apart from other candidates.
✨Tip Number 3
Showcase your ability to communicate complex technical concepts clearly. Since relationship building and communication are key aspects of this role, practice explaining your past projects and experiences in a way that non-technical stakeholders can understand. This will highlight your suitability for the position.
✨Tip Number 4
Stay updated on the latest advancements in GenAI and LLM technologies. Follow relevant blogs, podcasts, or research papers to keep your knowledge fresh. Being able to discuss recent developments in these areas during interviews will demonstrate your passion and commitment to the field.
We think you need these skills to ace Machine Learning 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 hands-on skills with Azure Databricks and your ability to manage large datasets.
Craft a Compelling Cover Letter: In your cover letter, explain why you're passionate about MLOps and how your background aligns with the role's requirements. Mention specific experiences that demonstrate your expertise in building scalable AI/ML solutions.
Showcase Relevant Skills: Clearly list your technical skills, especially those related to Python, SQL, Azure DevOps, and ML frameworks. Highlight your understanding of DataOps, DevOps, and ModelOps practices as they are crucial for this position.
Demonstrate Communication Skills: Since relationship building is key for this role, include examples of how you've successfully collaborated with cross-functional teams. This will show your ability to communicate effectively with diverse stakeholders.
How to prepare for a job interview at CipherTek Recruitment
✨Showcase Your Hands-On Experience
Make sure to highlight your practical experience with MLOps, especially in building and managing pipelines. Be prepared to discuss specific projects where you implemented solutions using Azure Databricks and how you tackled challenges.
✨Demonstrate Your Communication Skills
Since this role involves collaboration with various teams, emphasise your ability to communicate complex technical concepts clearly. Prepare examples of how you've successfully built relationships with stakeholders in previous roles.
✨Prepare for Technical Questions
Expect in-depth questions about AI/ML algorithms, data engineering, and DevOps practices. Brush up on your knowledge of Python, SQL, and any relevant ML frameworks, as well as your understanding of CI/CD processes.
✨Align with the Company's Goals
Research the investment bank's objectives and how your expertise can contribute to their success. Be ready to discuss how you can help align the MLOps framework with their strategic goals and governance.