Machine Learning Engineer - 6-month Fixed Term Contract

Singer Instrument Co
Minehead, United Kingdom
yesterday

Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Intermediate
Compensation
£ 52K

Job location

Remote
Minehead, United Kingdom

Tech stack

API
Artificial Intelligence
Amazon Web Services (AWS)
Amazon Web Services (AWS)
Data analysis
Architectural Patterns
Computer Vision
Software as a Service
Continuous Delivery
Cursor (Graphical User Interface Elements)
Imaging Technology
Python
Machine Learning
Language Modeling
OpenCV
Open Source Technology
Scrum
TensorFlow
GitHub Copilot
PyTorch
Large Language Models
Deep Learning
Backend
Low Latency
ONNX (Open Neural Network Exchange) Format
Atlassian Tools
Performance Monitor
Machine Learning Operations
Front End Software Development
TensorRT
Software Version Control

Job description

Supported by a newly secured public funding grant, we are initialising an intensive engineering phase to transition a proprietary, laboratory-validated technical imaging technology from a Technology Readiness Level (TRL) 4 Proof of Concept into an operationally ready, commercially viable TRL 7 multi-tenant AI SaaS platform. The platform leverages advanced machine learning models to automate high-precision feature detection, image normalisation, and automated data analysis for specialised business and research environments., We are seeking a highly skilled Machine Learning Engineer specialising in Computer Vision to spearhead the development of our next-generation visual AI capabilities. In this role, you will bridge the gap between bleeding-edge AI research and production-grade software. You will be responsible for sourcing, fine-tuning, and turning "off-the-shelf" foundation models into highly optimised, tailored commercial features that extract deep value from visual datasets, specifically for automated AI colony detection and counting, * Take state-of-the-art, off-the-shelf computer vision foundation models and adapt, fine-tune, or compress them to suit our specific product use cases.

  • Package and deploy machine learning models into production environments (ideally AWS cloud infrastructure), ensuring low latency, high throughput, and efficient GPU cost-optimisation.
  • Architect scalable pipelines for data collection, automated data labelling, visual preprocessing, and dataset augmentation.
  • Actively evaluate newly released open-source models, translating theoretical AI breakthroughs into practical, scalable features.
  • Partner with backend, frontend, and product teams to expose model outputs smoothly via high-performance APIs.

Requirements

  • 3+ years of commercial experience, specifically training, adapting, and deploying computer vision systems.

  • Proven experience working with, fine-tuning, and customising large off-the-shelf vision models, including:

  • Meta SAM 3 (Segment Anything Model 3) or SAM 2 for advanced promptable object masking and real-time tracking. Modern architectures like YOLO26, YOLO11, or state-of-the-art Real-Time DEtection TRansformers (DETRs).

  • Self-supervised backbones such as DINOv2.

Mastery of Python and deep learning ecosystems, specifically PyTorch or TensorFlow, alongside core toolkits like OpenCV.

Strong experience deploying vision models at scale using AWS tools (e.g., Amazon EC2 GPU instances, Amazon SageMaker) alongside model optimisation frameworks like TensorRT or ONNX.

Extensive experience working within fast-paced Agile delivery teams using frameworks such as Scrum/Kanban, and expert-level proficiency with project management tools, specifically Jira and Confluence.

Desirable / Nice-to-Have

  • Experience implementing modern MLOps pipelines for automated model retraining, version control (e.g., DVC, MLflow), continuous deployment (CD for ML), and real-time model drift/performance monitoring.
  • Prior commercial or academic experience applying computer vision to Life Sciences, Biotech, Medical Imaging, or Digital Pathology (e.g., cell segmentation, tissue analysis, fluorescent imaging, or lab automation datasets) is highly advantageous.
  • Familiarity with Vision-Language Models (VLMs) or fine-tuning Multimodal Foundation Models for visual reasoning tasks.
  • Proactive use of advanced, modern development workflows and agentic coding tools (e.g., Claude Code, Cursor, or GitHub Copilot) to accelerate development and testing loops., You will bring 3+ years of commercial experience to the role, specifically training, adapting, and deploying computer vision systems. Crucially, we firmly believe that the right person can come from any background, and your unique journey matters more than just a qualification., * Sovereignty Status: Candidates must possess an absolute, unrestricted right to work in the UK (UK Nationals preferred). We cannot offer visa sponsorship or international remote working arrangements for these fixed-term packages.

Benefits & conditions

  • Geographic Restriction: Every hour of work, line of code, and data annotation must be executed strictly on UK soil. Working from overseas (including temporary remote working holidays) is contractually prohibited., Full-time - Fixed Term Contract 6-Month Work Package

About the company

Singer Instruments empower scientists in laboratories in over 60 countries to accelerate their research efforts on global challenges. We are looking for a Machine Learning Engineer specialising in Computer Vision to turn off-the-shelf foundation models into highly optimised commercial features for our new AI SaaS platform Located in Exmoor on the UK's South West coast, Singer offers world class culture and benefits. An engaged team makes great products!, Singer Instruments, headquartered in Somerset on the edge of Exmoor, develop laboratory automation to accelerate research for scientists who want to make the world a better place. The company supports a global customer base, across a spectrum of interests such as healthcare, antibiotics, biofuels, renewable fabrics, and plant-based alternatives to meat. As an employee-owned company, Singer puts their people first. Singer Instruments are very proud to have won the Somerset Business Awards Employer of the Year; By supporting our teams and investing in our people, we get the best results for our customers. Staff are highly motivated by their global scientific impact and a shared value for company culture. Table football in the staff room, boules in the Japanese garden, and table tennis and barbecues on the deck form part of our working ethos. The atmosphere is relaxed, attitudes are positive, and nobody wears a suit. Work in a rapidly growing business should be fun, so Singer take any opportunity possible to celebrate success. Did somebody say BBQ?!

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