Enable job alerts via email!

Machine Learning Engineer

JR United Kingdom

City Of London

On-site

GBP 125,000 - 150,000

Full time

30+ days ago

Job summary

A data intelligence firm is seeking a Junior Machine Learning Engineer in London. You will work on transforming unstructured data into actionable insights, gain hands-on experience in ML, and collaborate with an expert team in a hybrid environment. Ideal candidates should have Python skills and a solid understanding of ML concepts to help build innovative solutions in the financial sector.

Benefits

Mentorship
Hybrid flexibility
Collaborative environment

Qualifications

  • 0–2 years of experience in machine learning, applied AI, or data science.
  • Familiarity with ML libraries and understanding of data preprocessing.
  • Interest in NLP and eagerness to learn in a collaborative environment.

Responsibilities

  • Help train, test, and optimise ML models for complex documents.
  • Design ML pipelines and fine-tune NLP models.
  • Collaborate with data scientists and engineers.

Skills

Python
Machine learning concepts
NLP
Data preprocessing

Tools

PyTorch
TensorFlow
Hugging Face Transformers
Job description

Social network you want to login/join with:

Machine Learning Engineer, london (city of london)

col-narrow-left

Client:

Intellect Group

Location:

london (city of london), United Kingdom

Job Category:

Other

-

EU work permit required:

Yes

col-narrow-right

Job Views:

1

Posted:

22.08.2025

Expiry Date:

06.10.2025

col-wide

Job Description:

Are you a Junior Machine Learning Engineer eager to turn messy, complex data into real-world intelligence?

We’re looking for a curious and motivated Junior ML Engineer to join a hybrid-working team building cutting-edge data intelligence tools for the financial sector. You’ll spend part of your time collaborating in person with engineers and data scientists, and part working remotely — giving you the best of both worlds.

You’ll be working on a platform that transforms unstructured private market data into actionable insights — learning how to design ML pipelines, fine-tune NLP models, and deploy solutions that really work in production.

In this role, you’ll help train, test, and optimise models that can read, understand, and structure complex documents at scale. From data preprocessing to model evaluation, you’ll gain hands-on experience across the machine learning lifecycle — while contributing to a product used by real-world clients.

What’s in it for you?

? AI That Matters – Work on models that make sense of unstructured financial documents and turn them into structured insights.

Hands-On ML Experience – Learn the full ML workflow — from cleaning data to deploying models and monitoring them in production.

? Mentorship & Growth – Work closely with experienced ML engineers who will guide your technical and career development.

? Collaborative Environment – Pair with engineers, data scientists, and domain experts to solve real-world challenges.

? Hybrid Flexibility – Balance focused remote work with in-person collaboration at our office.

What We’re Looking For:

  • 0–2 years of experience in machine learning, applied AI, or data science (personal projects and internships count!)
  • Solid Python skills and familiarity with libraries like PyTorch, TensorFlow, or Hugging Face Transformers
  • Understanding of basic ML concepts and data preprocessing techniques
  • Interest in NLP, unstructured data, and information extraction
  • Eagerness to learn, take feedback, and contribute to a collaborative team

Nice to Have:

  • Experience with SQL/NoSQL databases
  • Familiarity with MLOps tools (Docker, Git, CI/CD)
  • Exposure to vector databases or semantic search
  • Knowledge of financial datasets or document processing workflows

If you’re excited to grow your skills in machine learning and work on technology that helps people understand complex data — we’d love to hear from you.

Apply now and start your journey building the future of data-driven insight.

Get your free, confidential resume review.
or drag and drop a PDF, DOC, DOCX, ODT, or PAGES file up to 5MB.