INTERNSHIP IN REPURPOSING OPEN ARCHITECTURE LLM AND/OR DEVELOPING A GRAPHICAL USER INTERFACE

Quantimental Technologies
London
10 months ago
Applications closed

Related Jobs

View all jobs

Giant Leap Trainee, Data Scientist

Giant Leap Trainee, Data Scientist

2026 Summer Internship, Engineering & Data Science (London)

Artificial Intelligence and Machine Learning Graduate

Sewerage Data Science Placement — 12‑Month Bath Internship

Data Scientist Trainee: Weather ML & Data Cleaning

General Description:

Quantimental Technologies builds vertical, downstream, and agentic AI products (https://www.quanti-tech.com/) for productivity enhancement and decisions-making tools and automation.


Position Overview:

An opportunity for recent graduates or students in their last two years of study (undergraduate or postgraduate)to gain8–10 weeks ofunpaid internship experience. As an intern, you will have the chance to work on various innovative projects, such as:

  • Repurposing an open architecture large language model (LLM):Utilize Meta’s Llama to build an AI assistant for emails and calendars under a RAG framework.
  • Enhancing a specialized US capital markets chatbot:Improve the capabilities of our internally developed chatbot.
  • Refining cross-platform interfaces:Polish an existing cross-platform graphical user interface for desktops, laptops, and smartphones using Dart (Flutter).
  • Integrating products into cloud and vector search platforms:Ensure seamless integration with cloud compute and specialized vector search platforms.


Task allocation will be at the discretion of the Founder, considering the interns' skill sets and interests identified during the interview phase. Interns will be for the most part enhancing existing scripts (or using example scripts to build newer scripts) or developing new scripts from scratch.


The role offers:

  • Hands-on Experience: Gain real-life experience working on production-level workflows, a rare opportunity for fresh graduates.
  • Skill Development: Enhance your quantitative and programming skills through practical application.
  • Networking Opportunities: Connect and collaborate with fellow interns to build valuable professional relationships.
  • Resume Boost: Gain a competitive edge for your resume.


The part-time role requires a commitment of 8 - 12 hours per week and is primarily remote.However, periodic onsite days are available for candidates residing in the Greater London area (England, UK). You will collaborate with a team of interns under the guidance of the Founder.


Job Description:

  • Assist the Founder in repurposing an open architecture LLM like Meta’s Llama to enhance the periodic scanning, reviewing, and reporting of extraordinary events for publicly-listed companies in the USA.
  • Ensure scripts are documented to exacting standards including #headers and #brief explanations of each section’s purpose to make it easier for others to review and amend where applicable.
  • Improve the report generation, and test and debug erroneous reports.
  • Develop no code plug-and-play graphical user interfaces as directed by the Founder.
  • Create user-friendly prompts for individuals with basic or no programming skills.
  • Conduct rigorous testing on the prototype for continuous improvement and debugging.
  • Collaborate with team members or other interns to enhance process flows and improve workstreams.
  • Continuously update the spreadsheet shared on OneDrive with notes on data sources, design, scripts, libraries used, and challenges to foster knowledge sharing and improve scalability.
  • Adhere to deadlines and commit to attendance of group or one-on-one touchpoint meetings on Zoom over video.


Required Qualities and Skills:

  • Recently graduated or final two years of studies (undergraduate or postgraduate), in Computer Science or Artificial Intelligence, with a GPA of 3.3 or higher or on track to receive a distinction/first class or its local equivalent.
  • Developing knowledge of Python (gained more hands-on experience and understanding fundamental principles),and/orbasic knowledge of Dart (Flutter) (understanding fundamental principles).
  • Can do attitude and eager to learn new things and figure things out.
  • Curious and eager to learn and improve workflows.
  • Strong analytical and numerical skills.
  • Responsive, committed, and consistent.
  • Self-motivated, highly organized, and proactive in problem-solving.
  • Effective communication skills in English, both verbal and written.


Work Location

  • Remote (optional periodic onsite days if the candidate resides within the Greater London area. England, UK)


Equipment, Data Access, and Timeline

  • What we provide:Access to data, Organizational GitHub, license rights (where applicable), mentorship, direction, and strong recommendations. The internship would last from 8 to 10 weeks, depending on the intern's preference, decided at the outset.
  • What the intern needs:Reliable high-speed internet, a reliable computer with minimum 4GB of dedicated VRAM GPU, and a camera.


Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

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

Industry Insights

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

AI Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Changing career into artificial intelligence in your 30s, 40s or 50s is no longer unusual in the UK. It is happening quietly every day across fintech, healthcare, retail, manufacturing, government & professional services. But it is also surrounded by hype, fear & misinformation. This article is a realistic, UK-specific guide for career switchers who want the truth about AI jobs: what roles genuinely exist, what skills employers actually hire for, how long retraining really takes & whether age is a barrier (spoiler: not in the way people think). If you are considering a move into AI but want facts rather than Silicon Valley fantasy, this is for you.

How to Write an AI Job Ad That Attracts the Right People

Artificial intelligence is now embedded across almost every sector of the UK economy. From fintech and healthcare to retail, defence and climate tech, organisations are competing for AI talent at an unprecedented pace. Yet despite the volume of AI job adverts online, many employers struggle to attract the right candidates. Roles are flooded with unsuitable applications, while highly capable AI professionals scroll past adverts that feel vague, inflated or disconnected from reality. In most cases, the issue isn’t a shortage of AI talent — it’s the quality of the job advert. Writing an effective AI job ad requires more care than traditional tech hiring. AI professionals are analytical, sceptical of hype and highly selective about where they apply. A poorly written advert doesn’t just fail to convert — it actively damages your credibility. This guide explains how to write an AI job ad that attracts the right people, filters out mismatches and positions your organisation as a serious employer in the AI space.

Maths for AI Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are a software engineer, data scientist or analyst looking to move into AI or you are a UK undergraduate or postgraduate in computer science, maths, engineering or a related subject applying for AI roles, the maths can feel like the biggest barrier. Job descriptions say “strong maths” or “solid fundamentals” but rarely spell out what that means day to day. The good news is you do not need a full maths degree worth of theory to start applying. For most UK roles like Machine Learning Engineer, AI Engineer, Data Scientist, Applied Scientist, NLP Engineer or Computer Vision Engineer, the maths you actually use again & again is concentrated in a handful of topics: Linear algebra essentials Probability & statistics for uncertainty & evaluation Calculus essentials for gradients & backprop Optimisation basics for training & tuning A small amount of discrete maths for practical reasoning This guide turns vague requirements into a clear checklist, a 6-week learning plan & portfolio projects that prove you can translate maths into working code.