Machine Learning Engineer (NLP)

Bristol
4 weeks ago
Create job alert

Job Specification: Machine Learning Engineer (NLP) (Pytorch)

Location: Bristol, UK (Hybrid - 2 days per week in the office)

About the Role

I'm looking for an NLP Engineer to join a forward-thinking company that specialises in advanced risk analytics and machine learning. This is a great opportunity to work on cutting-edge AI solutions in a rapidly evolving industry, with a focus on real-world applications in cyber reinsurance.

Key Responsibilities * Develop and optimise NLP models for tasks like information retrieval, summarisation, and other domain-specific applications. * Work closely with data scientists, engineers, and domain experts to understand business needs and deliver AI-driven solutions. * Stay up to date with the latest NLP technologies, including semantic search and generative AI, and apply them to improve existing models. * Build and maintain scalable data pipelines for processing both structured and unstructured data efficiently. * Evaluate and fine-tune machine learning models to ensure optimal performance. * Ensure models and data pipelines adhere to best practices for security, robustness, and compliance. * Document processes and methodologies to support knowledge sharing and transparency, reproducibility, and knowledge sharing across teams.

What You Need * A degree in Computer Science, Engineering, Statistics, or a related field (Master's or Ph.D. preferred but not essential). * Strong understanding of machine learning algorithms and NLP techniques, with hands-on experience in either academia or industry. * Proficiency in Python and experience with ML/NLP libraries like TensorFlow, PyTorch, scikit-learn, or Hugging Face. * Experience working with cloud platforms such as AWS, GCP, or Azure. * Familiarity with advanced NLP methods, including Prompt Engineering, Parameter-Efficient Fine-Tuning (PEFT), and Direct Preference Optimization (DPO). * Strong problem-solving skills and the ability to work independently or collaboratively. * Great communication skills, both written and verbal.

Nice-to-Haves * Experience adapting large language models (LLMs) for specific domains. * Knowledge of event extraction and multimodal information processing. * Experience with dataset collection and improvement strategies. * Familiarity with knowledge graphs and their applications. * Experience handling large-scale datasets and using distributed computing frameworks like Databricks or Spark. * Background in insurance or cybersecurity. * Understanding of data privacy regulations such as GDPR and CCPA.

Salary & Benefits * £40,000 - £60,000 depending on experience. * Benefits include: ○ 5% pension. ○ 28 days holiday + bank holidays. ○ Private medical insurance. ○ Death in service benefit.

Why Apply? * A chance to work on cutting-edge AI and machine learning projects with real-world impact. A friendly inclusive team * A hybrid working model (2 days per week in the Bristol office). * A collaborative and inclusive work environment. * Plenty of career growth and development opportunities.

Please apply by sending your CV to (url removed)

Related Jobs

View all jobs

Machine Learning Engineer (NLP)

Senior Machine Learning Engineer

Machine Learning / Computer Vision Engineer – Data Scientist

Senior Machine Learning Engineer

C++ Senior Engineer – ML Focus

Senior Technical Services Engineer

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.

Tips for Staying Inspired: How Edge Computing Pros Fuel Creativity and Innovation

Edge computing continues to disrupt traditional cloud-centric models, enabling low-latency data processing, reducing network congestion, and unlocking real-time insights across diverse industries. From smart manufacturing floors to autonomous vehicles and healthcare devices, the potential impact of edge computing is immense. Yet, professionals in this field face constant challenges—balancing constraints of limited on-device resources, ensuring security at the edge, and rapidly integrating new hardware and software innovations. How do edge computing experts keep fresh ideas flowing amid these demands? Below, we explore ten practical strategies that empower edge architects, IoT developers, infrastructure engineers, and solution consultants to stay inspired and continually innovate. Whether you’re building next-generation IoT solutions or refining multi-access edge computing (MEC) platforms, these tips can help you approach complex problems with creativity and renewed passion.

Top 10 Edge Computing Career Myths Debunked: Key Facts for Aspiring Professionals

Edge computing is rapidly reshaping how data is processed, analysed, and acted upon—bringing computation and storage closer to the actual sources of data, whether that’s a factory floor, a smart device, or an autonomous car. As the demand for latency-sensitive applications grows—think autonomous vehicles, augmented reality, and real-time analytics—so does the need for skilled professionals who can architect, implement, and maintain robust edge computing solutions. Yet, as with any emerging tech discipline, misconceptions about edge computing careers abound. Some assume the field is only for hardware wizards or giant telecoms; others believe you need a PhD in distributed systems to get started. At EdgeComputingJobs.co.uk, we see firsthand how such myths can dissuade bright minds from joining an industry that’s on the cusp of significant global impact. This article aims to debunk the top 10 myths around edge computing careers, providing clear-eyed insights into the actual opportunities and requirements within this exciting space. Whether you’re a seasoned tech professional exploring new horizons or a newcomer drawn to the prospect of real-time data processing, we invite you to read on and discover why edge computing might be the perfect new frontier for your career.

Global vs. Local: Comparing the UK Edge Computing Job Market to International Landscapes

A guide to opportunities, salaries, and work culture in edge computing across the UK, the US, Europe, and Asia For years, cloud computing has dominated conversations about digital transformation, providing the on-demand resources and scalability that organisations need to innovate. However, another paradigm is rapidly gaining momentum: edge computing. By processing data closer to its source (think sensors on a factory floor or cameras in a smart city), edge computing can reduce latency, improve reliability, and even lower bandwidth costs. It’s already transforming industries such as manufacturing, autonomous vehicles, healthcare, and telecom—sparking strong demand for professionals who can design, deploy, and manage distributed systems at the “edge.” In this blog post, we’ll explore how the UK’s edge computing job market compares to major international hubs: the United States, Europe, and Asia. We’ll evaluate current hiring trends, salary ranges, and work culture factors, offering insights for anyone considering an edge computing career—whether locally in the UK or abroad. Whether you’re an embedded systems engineer, a cloud specialist pivoting to edge, or a data scientist branching into IoT analytics, understanding these global vs. local nuances can help you plan your next career move. By the end, you’ll have a comprehensive view of the evolving edge computing landscape, including which regions are leading adoption, what skill sets are most valued, and how compensation stacks up around the world. Let’s delve in.