Machine Learning Engineer, Specialist

NLP PEOPLE
Manchester
1 month ago
Create job alert

About the Machine Learning Engineer for CDAO Europe
CDAO Europe is looking for a machine learning engineer to build efficient, data-driven AI systems that advance our predictive automation capabilities. The candidate should be highly skilled in statistics and programming, with the ability to confidently assess, analyze, and organize large amounts of data. The candidate should also be able to execute tests and optimize Vanguard’s machine learning models and algorithms.

This person will play a critical role in designing and developing machine learning algorithms and AI applications and systems for Vanguard, solve complex problems with multilayered data sets, and optimize existing machine learning libraries and frameworks. They will collaborate with data scientists, data analysts, data engineers, and data architects on production systems and applications, and identify differences in data distribution that could potentially affect model performance in real-world applications.
This person will be a major contributor in our GenAI intake process, assessing and reviewing use cases from around the business, and play a key role in Vanguard’s model governance processes.

Core Responsibilities

  1. Leverages data pipeline designs and supports the development of data pipelines to support model development. Proficient with software tools that develop data pipelines in a distributed computing environment (PySpark, GlueETL).
  2. Supports integration of model pipelines in a production environment. Develops understanding of SDLC for model production.
  3. Reviews pipeline designs, makes data model design changes as needed. Documents and reviews design changes with data science teams.
  4. Supports data discovery & automated ingestion for model development. Performs detailed analysis of raw data sources for data quality, applies business context, and model development needs.
  5. Engages with internal stakeholders to understand and probe business processes in order to develop hypotheses. Brings structure to requests and translates requirements into an analytic approach. Participates in and influences ongoing business planning and departmental prioritization activities.
  6. Runs model monitoring scripts, follows process for alerts to management as needed. Addresses issues found in data pipelines from model monitoring alerts.
  7. Participates in special projects and performs other duties as assigned.

Qualifications

• Undergraduate degree or equivalent combination of training and experience.
• Minimum of five years related work experience.

How We Work

Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.

Company:

Vanguard Careers

Level of experience (years):

Senior (5+ years of experience)

#J-18808-Ljbffr

Related Jobs

View all jobs

Machine Learning Engineer - Defence Sector - Cambridge

Staff Machine Learning Engineer (NLP, LLMs) - new PurpleAI product

Senior Machine Learning Engineer

Senior AI | Machine Learning Engineer

Senior AI | Machine Learning Engineer

Principal Data Scientist - NLP

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Negotiating Your AI Job Offer: Equity, Bonuses & Perks Explained

Artificial intelligence (AI) has proven itself to be one of the most transformative forces in today’s business world. From smart chatbots in customer service to predictive analytics in finance, AI technologies are reshaping how organisations operate and innovate. As the demand for AI professionals grows, so does the complexity of compensation packages. If you’re a mid‑senior AI professional, you’ve likely seen job offers that include far more than just a base salary—think equity, bonuses, and a range of perks designed to entice you into joining or staying with a company. For many, the focus remains squarely on salary. While that’s understandable—after all, your monthly take‑home pay is what covers day-to-day expenses—limiting your negotiations to salary alone can leave considerable value on the table. From stock options in ambitious startups to sign‑on bonuses that ‘buy you out’ of your current contract, modern AI job offers often include elements that can significantly boost your long-term wealth and job satisfaction. This article aims to shed light on the full scope of AI compensation—specifically focusing on how equity, bonuses, and perks can enhance (or sometimes detract from) the overall value of your package. We’ll delve into how these elements work in practice, what to watch out for, and how to navigate the negotiation process effectively. Our goal is to provide mid‑senior AI professionals with the insights and tools to land a holistic compensation deal that accurately reflects their technical expertise, leadership potential, and strategic importance in this fast-moving field. Whether you’re eyeing a leadership role in machine learning at an established tech giant, or you’re considering a pioneering position at a disruptive AI startup, the knowledge in this guide will help you weigh the merits of base salary alongside the potential riches—and risks—of equity, bonuses, and other benefits. By the end, you’ll have a clearer sense of how to align your compensation with both your immediate lifestyle needs and long-term career aspirations.

AI Jobs in the Public Sector: MOD, NHS & Gov Digital Service Opportunities

Artificial intelligence (AI) has rapidly evolved from a niche field of computer science into a transformative force reshaping industries across the globe. From healthcare to finance and from education to defence, AI-driven tools and techniques are revolutionising how we approach problems, improve efficiency, and make data-driven decisions. Nowhere is this transformation more apparent than in the United Kingdom’s public sector. Key government entities, including the Ministry of Defence (MOD), the National Health Service (NHS), and the Government Digital Service (GDS), are increasingly incorporating AI into their operations. Consequently, AI jobs within these bodies are growing both in number and strategic importance. In this comprehensive blog post, we will explore the landscape of AI jobs across the UK public sector, with a close look at the MOD, the NHS, and the Government Digital Service. We will delve into the reasons these organisations are investing heavily in AI, the types of roles available, the essential skills and qualifications required, as well as the salary ranges one might expect. Whether you are a new graduate keen to make a meaningful impact through your technical skills or a seasoned professional looking for your next career move, the public sector offers a wealth of opportunities in AI. By the end of this article, you will have a clearer understanding of why AI is so crucial to the public sector’s success, which roles are in demand, and how you can tailor your application to stand out in a competitive and rewarding job market.

Contract vs Permanent AI Jobs: Which Pays Better in 2025?

n the ever-evolving world of technology, the competition for top talent in artificial intelligence (AI) is intense—and the rewards are significant. By 2025, AI roles in machine learning, natural language processing, data science, and robotics are expected to be among the highest-paid professions within the UK technology sector. As an AI professional, deciding between contracting (either as a day‑rate contractor or via fixed-term contracts) and permanent employment could drastically impact your take‑home pay, job security, and career trajectory. In this article, we will delve into the various types of AI roles in 2025—particularly focusing on day‑rate contracting, fixed-term contract (FTC) roles, and permanent positions. We will compare the earning potential across these three employment types, discuss the key pros and cons, and provide practical examples of how your annual take‑home pay might differ under each scenario. Whether you are already working in AI or looking to break into this booming field, understanding these employment options will help you make an informed decision on your next move.