Cortech Talent Solutions Ltd
Machine Learning Engineer

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Role: Machine Learning Engineer
Location: Glasgow
Onsite: 2-3 days a week
Seeking £55,000 - £60,000 but negotiable
About the role:
As Machine Learning Engineer, you design, train and deploy the computer vision and machine learning models behind products like turning camera and sensor data into the accurate, trusted insights our customers rely on.
You report to the Lead of ML & AI and work closely with the Head of Hardware/Devices on camera and sensor requirements, and the Head of Software on integrating models into production systems.
You’ll work across the full ML lifecycle, from data and feature engineering through model training, evaluation and production deployment, with direct visibility across a small, collaborative team.
What you’ll be doing:
- Design, develop and deploy high-performing machine learning models for computer vision applications — image classification, object detection, segmentation and video analysis.
- Carry out data analysis, feature engineering and model selection to optimise model performance and accuracy.
- Develop and maintain robust, scalable ML pipelines using cloud services (e.g. AWS SageMaker, EC2, S3, Lambda, Rekognition, MLFlow).
- Collaborate with data engineers, software engineers and product managers to translate business requirements into technical specifications.
- Stay abreast of advances in computer vision and machine learning research, and identify opportunities to apply them.
- Contribute to the development of machine learning infrastructure and best practice.
- Mentor junior team members and contribute to a culture of learning within the team.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
What we’re looking for
You’ll ideally have:
- A Master’s or PhD in Computer Science, Computer Engineering or a related field, with a strong focus on machine learning.
- Solid understanding of deep learning concepts and architectures (CNNs, RNNs, Transformers) and their practical application.
- Proficiency in Python and common ML libraries (TensorFlow, PyTorch, scikit-learn).
- Strong experience with AWS services (SageMaker, EC2, S3, Lambda or equivalent).
- Experience with cloud-native development and deployment methodologies.
It would be great if you also have:
- Knowledge or experience in the aquaculture sector.
- Knowledge of MLOps principles and best practice.
- Experience with distributed computing and large-scale data processing.
- Experience with underwater or low-visibility imaging, or animal detection/tracking.


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Personal Attributes:
The successful candidate will be:
- A strong problem-solver, comfortable working with noisy, real-world data.
- Self-starting, able to work independently and as part of a small team.
- A strong communicator, able to explain model capability and limitations to non-technical stakeholders.
- Passionate about machine learning, with a desire to keep learning and growing.
Why Join Us?
This is a chance to build the computer vision and machine learning models behind a category-defining aquaculture technology platform — with direct visibility across a small team and models that go straight into products customers rely on.
What we offer:
- Competitive salary, based on experience
- 33 days annual leave (including bank holidays)
- Death in service at 4 x your annual salary
- Employee Assistance Programme
- Enhanced parental leave policies
- Birthday day off
- Paid bereavement and sick leave
- Company salary sacrifice pension scheme
- Cycle to work scheme
- Regular social breakfasts, lunches and team events
How to Apply
Apply now or send your CV to danni@cortechtalentsolutions.co.uk
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