Machine Learning Engineering Intern- AI Agents - 2025 Programme

CGG SA
Crawley
1 week ago
Create job alert

We are seeking talented individuals with fresh perspectives and deep curiosity to join our team! As a Machine Learning Engineering Intern at the Viridien AI Lab, you'll play a key role in advancing algorithms and models in the fast-growing domain of AI agents.

Viridien(http://www.viridiengroup.com/ai)is an advanced technology, digital and Earth data company that pushes the boundaries of science for a more prosperous and sustainable future. With our ingenuity, drive and deep curiosity we discover new insights, innovations, and solutions that efficiently and responsibly resolve complex natural resource, digital, energy transition and infrastructure challenges.

Job details

We are seeking talented individuals with fresh perspectives and deep curiosity to join our team! As a Machine Learning Engineering Intern at the Viridien AI Lab, you'll play a key role in advancing algorithms and models in the fast-growing domain of AI agents. You will work on cutting-edge projects involving document processing, knowledge retrieval, and workflow automation using frameworks like CAMEL. This internship will offer you the chance to explore multi-agent frameworks and apply them to real-world challenges across industries.

You will collaborate with experienced engineers and data scientists to design, implement, and optimize agent-based solutions that drive high-impact business outcomes. The ideal candidate is enthusiastic about learning, adaptable to evolving priorities, and excited to work in a dynamic research environment.

Location

Successful candidates will join our largest European Centre in Crawley, near London Gatwick Airport, just outside the M25, with excellent transport links to Central London and the South Coast.

Qualifications

Pursuing a PhD or MSc in Computer Science, Artificial Intelligence, Data Science, or related field.

Key Skills and Experiences

  • Strong foundation in machine learning and statistics, with hands-on experience in natural language processing (NLP) or computer vision (CV); familiarity with large language models (LLMs) is a plus.

  • Understanding of AI agents and multi-agent frameworks such as CAMEL is a plus.

  • Skilled in object-oriented programming using Python.

  • Familiarity with PyTorch or similar machine learning frameworks.

  • Excellent problem-solving skills and ability to work on open-ended challenges.

  • Strong communication skills, both written and verbal

Why work with us?

  • Hands-on experience on high-impact AI agent projects in document processing, knowledge retrieval, and workflow automation.

  • Mentorship from industry experts in AI and data science.

  • Opportunities for professional growth and networking.

  • Flexible working through our hybrid scheme, blending home and office work.

  • Bank Holiday Swap - change your public holiday for another day of your choice!

  • Visa sponsorship and comprehensive relocation packages available.

  • Relaxed dress code policy.

Learning and Development

At Viridien, we foster a culture of continuous learning and provide tailored training programs through our Learning Hub, designed to enhance technical, commercial, and personal growth.

We Care about the Environment

We encourage and actively support a strong sense of community, through volunteering and various company initiatives, as well as a strong company commitment to protecting our environment through sustainable solutions, energy saving and waste reduction enterprises.

We see things differently. Diversity fuels our innovation, we value the unique ways in which we differ, and we are committed to equal employment opportunities for all professionals.

UGFsbGF2aS5DaGF3bGEuMTg1MTAuMTIyNzFAY2dnLmFwbGl0cmFrLmNvbQ.gif

Related Jobs

View all jobs

Machine Learning Engineering Manager | Computer Vision | Deep Learning | Python | C++ | London, Hybrid

Machine Learning Engineering Manager

Data Science & AI Consultant

Machine Learning and AI Engineering Lead

Machine Learning Manager, London

Machine Learning Research Scientist - PhD, NLP, LLM

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.

Portfolio Projects That Get You Hired for AI Jobs (With Real GitHub Examples)

In the fast-evolving world of artificial intelligence (AI), an impressive portfolio of projects can act as your passport to landing a sought-after role. Even if you’ve aced interviews in the past, employers in AI and machine learning (ML) are increasingly asking candidates to demonstrate hands-on experience through the projects they’ve built and shared online. This is because practical ability often speaks volumes about your suitability for a role—far more than any exam or certification alone could. In this article, we’ll explore how to build an outstanding AI portfolio that catches the eye of recruiters and hiring managers, including: Why an AI portfolio is crucial for job seekers. How to choose AI projects that align with your target roles. Specific project ideas and real GitHub examples to help you stand out. Best practices for showcasing your work, from writing clear READMEs to using Jupyter notebooks effectively. Tips on structuring your GitHub so that employers can instantly see your value. Moreover, we’ll discuss how you can use your portfolio to connect with top employers in AI, with a handy link to our CV-upload page on Artificial Intelligence Jobs for when you’re ready to apply. By the end, you’ll have a clear roadmap to building a portfolio that will help secure interviews—and the AI job—of your dreams.

AI Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

In today's competitive AI job market, nailing a technical interview can be the difference between landing your dream role and getting lost in the crowd. Whether you're looking to break into machine learning, deep learning, NLP (Natural Language Processing), or data science, your problem-solving skills and system design expertise are certain to be put to the test. AI‑related job interviews typically involve a range of coding challenges, algorithmic puzzles, and system design questions. You’ll often be asked to delve into the principles of machine learning pipelines, discuss how to optimise large-scale systems, and demonstrate your coding proficiency in languages like Python, C++, or Java. Adequate preparation not only boosts your confidence but also reduces the likelihood of fumbling through unfamiliar territory. If you’re actively seeking positions at major tech companies or innovative AI start-ups, then check out www.artificialintelligencejobs.co.uk for some of the latest vacancies in the UK. Meanwhile, this blog post will guide you through 30 real coding & system-design questions you’re likely to encounter during your AI job interview. This list is designed to help you practise, anticipate typical question patterns, and stay ahead of the competition. By reading through each question and thinking about the possible approaches, you’ll sharpen your problem-solving skills, time management, and critical thinking. Each question covers fundamental concepts that employers regularly test, ensuring you’re well-equipped for success. Let’s dive right in.

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.