Senior Natrual Language Processing Developer

Newport
1 month ago
Applications closed

Related Jobs

View all jobs

Senior Cloud Engineer (AWS)

Contract Mid-weight/Senior Creative Technologist - AI Project

Senior AI Engineer

Senior Data Scientist

Machine Learning (Algorithm Development)

Business Intelligence(BI) Lead

Job Title: Senior Natural Language Processing (NLP) Developer

About the Role: We are seeking a talented Senior Natural Language Processing (NLP) Developer to join a dynamic team. In this role, you will be responsible for developing and maintaining high-quality AI and ML systems with a focus on Natural Language Processing. You will have the opportunity to work with cutting-edge cloud technologies and be part of a collaborative, multi-disciplinary team delivering innovative digital services.

This position offers the chance to engage in meaningful projects while continuously learning new technologies and methodologies. You will also contribute to the technical strategy and work on enhancing enterprise-grade services.

Key Responsibilities:

Technical:

Design, code, test, and document AI and ML activities focused on NLP.
Collaborate with test engineers to ensure code quality and test coverage.
Troubleshoot system issues and improve existing processes.
Investigate problems and recommend improvements.
Develop APIs and toolkits for performance optimization, security, and scalability.
Work within a multi-disciplinary team to deliver user-focused services.
Implement and maintain cloud-hosted development environments (e.g., Azure Machine Learning Studio).
Continuously embrace a fail-fast approach and strive for innovative solutions.Behavioural:

Lead by example, driving results and fostering a collaborative environment.
Share knowledge and expertise, championing a culture of learning and teamwork.
Manage and delegate tasks within the team effectively.
Take full responsibility for decisions and outcomes.
Maintain composure and learn from setbacks.
Inspire others to move things forward and deliver results.Personal and Team Development:

Drive your own development by staying updated with new technologies and trends.
Mentor and guide junior team members, fostering their personal growth.
Ensure that the team adheres to governance and processes for test and build activities.
Promote continuous improvement in technical knowledge.Essential Skills and Experience:

Proven experience in delivering technical solutions as part of large projects.
Proficiency with modern delivery models such as Scrum and Agile.
Experience with statistical modeling, machine learning, and AI techniques.
Solid understanding of databases and data engineering principles.
Strong experience with Python and deep learning frameworks.
Knowledge of cloud-hosted environments like Azure Machine Learning Studio.
Familiarity with Git and version control systems.
Ability to deliver models from concept to production and continuously improve them.Desirable Skills:

Experience with vector databases.
Understanding of statistics, linear algebra, and calculus.
Experience with SQL and Docker & Kubernetes.
Familiarity with CI/CD principles and MLOps.
Experience with Azure DevOps.Required Framework Skills:

Availability and capacity management.
Development process optimization.
Information security.
Modern standards approach and systems integration.
User-focused systems design and prototyping.Career Path and Development: This role offers excellent opportunities for career progression and skill development within a Digital Engineering Department. Training will be provided in areas such as Python, Scrum/Agile, Azure DevOps, SQL, and Azure Cloud fundamentals.

So, if this role sounds of interest, please apply today

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.

10 Ways AI Pros Stay Inspired: Boost Creativity with Side Projects, Hackathons & More

In the rapidly evolving world of Artificial Intelligence (AI), creativity and innovation are critical. AI professionals—whether data scientists, machine learning engineers, or research scientists—must constantly rejuvenate their thinking to solve complex challenges. But how exactly do these experts stay energised and creative in their work? The answer often lies in a combination of strategic habits, side projects, hackathons, Kaggle competitions, reading the latest research, and consciously stepping out of comfort zones. This article will explore why these activities are so valuable, as well as provide actionable tips for anyone looking to spark new ideas and enrich their AI career. Below, we’ll delve into tried-and-tested strategies that AI pros employ to drive innovation, foster creativity, and maintain an inspired outlook in an industry that can be both exhilarating and daunting. Whether you’re just starting your AI journey or you’re an experienced professional aiming to sharpen your skills, these insights will help you break out of ruts, discover fresh perspectives, and bring your boldest ideas to life.

Top 10 AI Career Myths Debunked: Key Facts for Aspiring Professionals

Artificial Intelligence (AI) is one of the most dynamic and rapidly growing sectors in technology today. The lure of AI-related roles continues to draw a diverse range of job seekers—from seasoned software engineers to recent graduates in fields such as mathematics, physics, or data science. Yet, despite AI’s growing prominence and accessibility, there remains a dizzying array of myths surrounding careers in this field. From ideas about requiring near-superhuman technical prowess to assumptions that machines themselves will replace these jobs, the stories we hear sometimes do more harm than good. In reality, the AI job market offers far more opportunities than the alarmist headlines and misconceptions might suggest. Here at ArtificialIntelligenceJobs.co.uk, we witness firsthand the myriad roles, backgrounds, and success stories that drive the industry forward. In this blog post, we aim to separate fact from fiction—taking the most pervasive myths about AI careers and debunking them with clear, evidence-based insights. Whether you are an established professional considering a career pivot into data science, or a student uncertain about whether AI is the right path, this article will help you gain a realistic perspective on what AI careers entail. Let’s uncover the truth behind the most common myths and discover the actual opportunities and realities you can expect in this vibrant sector.

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

How to navigate salaries, opportunities, and work culture in AI across the UK, the US, Europe, and Asia Artificial Intelligence (AI) has evolved from a niche field of research to an integral component of modern industries—powering everything from chatbots and driverless cars to sophisticated data analytics in finance and healthcare. The job market for AI professionals is consequently booming, with thousands of new positions posted each month worldwide. In this blog post, we will explore how the UK’s AI job market compares to that of the United States, Europe, and Asia, delving into differences in job demand, salaries, and workplace culture. Additionally, we will provide insights for candidates considering remote or international opportunities. Whether you are a freshly qualified graduate in data science, an experienced machine learning engineer, or a professional from a parallel domain looking to transition into AI, understanding the global vs. local landscape can help you make an informed decision about your career trajectory. As the demand for artificial intelligence skills grows—and borders become more porous with hybrid and remote work—the possibilities for ambitious job-seekers are expanding exponentially. This article will offer a comprehensive look at the various regional markets, exploring how the UK fares in comparison to other major AI hubs. We’ll also suggest factors to consider when choosing where in the world to work, whether physically or remotely. By the end, you’ll have a clearer picture of the AI employment landscape, and you’ll be better prepared to carve out your own path.