AI Applied Engineer

Dystematic Limited
London
1 week ago
Applications closed

Related Jobs

View all jobs

Applied AI Engineer

Senior Applied Scientist

Senior AI Engineer - Data Agents

Applied AI Research Scientist: AEC

Sr. Director of Engineering, AI & ML

NLP / LLM Scientist – Applied AI ML Lead – Machine Learning Centre of Excellence

We are expanding our capabilities in AI and are now looking to hire an Applied AI Engineer.

If you have a passion for Generative models and are excited about implementing the latest advancements in AI, come and join us! You’ll be working with a team of experienced developers, data scientists, and product managers to shape the future of AI applications. We offer a competitive salary and an environment that encourages continuous learning and innovation.

Key Responsibilities

  • Implement agents and tools based on generative models
  • Collaborate with cross-functional teams to integrate AI models into products and solutions
  • Fine-tune machine learning and generative models for specific applications
  • Stay up-to-date with current AI research and adapt new methodologies for practical applications

Requirements

  • MSc Degree in either Data Science, AI, ML or Computer Science
  • 3-5 years experience in applied AI
  • Deep understanding of ML algorithms, DL architectures, RL
  • Insight into generative models, transformer architecture, and training of LLMs
  • Proficiency in Python, familiarity with TensorFlow, PyTorch, Hugging Face transformers and LangChain
  • Effective communication, especially in explaining AI concepts to non-technical stakeholders

Next Steps

Interested in the vacancy? We encourage a diverse workforce and welcome applications from all communities.

#J-18808-Ljbffr

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.

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

How to evaluate opportunities, salaries, and work culture in machine learning across the UK, the US, Europe, and Asia Machine learning (ML) has rapidly transcended the research labs of academia to become a foundational pillar of modern technology. From recommendation engines and autonomous vehicles to fraud detection and personalised healthcare, machine learning techniques are increasingly ubiquitous, transforming how organisations operate. This surge in applications has fuelled an extraordinary global demand for ML professionals—data scientists, ML engineers, research scientists, and more. In this article, we’ll examine how the UK machine learning job market compares to prominent international hubs, including the United States, Europe, and Asia. We’ll explore hiring trends, salary ranges, workplace cultures, and the nuances of remote and overseas roles. Whether you’re a fresh graduate aiming to break into the field, a software engineer with an ML specialisation, or a seasoned professional seeking your next challenge, understanding the global ML landscape is essential for making an informed career move. By the end of this overview, you’ll be equipped with insights into which regions offer the best blend of salaries, work-life balance, and cutting-edge projects—plus practical tips on how to succeed in a domain that’s constantly evolving. Let’s dive in.

Machine Learning Leadership for Managers: Strategies to Motivate, Mentor, and Set Realistic Goals in Data-Driven Teams

Machine learning (ML) has become an indispensable force in the modern business world, influencing everything from targeted marketing campaigns to advanced medical diagnostics. As industries integrate predictive algorithms and data-driven decision-making into their core operations, the need for effective leadership in machine learning environments has never been greater. Whether you’re overseeing a small team of data scientists or spearheading an enterprise-scale ML project, your leadership style must accommodate rapid innovation, complex problem-solving, and diverse stakeholder expectations. This guide provides actionable insights into how you can motivate, mentor, and establish achievable goals for your machine learning teams—ensuring they thrive in data-driven environments.

Top 10 Books to Advance Your Machine Learning Career in the UK

Machine learning (ML) remains one of the fastest-growing fields within technology, reshaping industries across the UK from finance and healthcare to e-commerce, telecommunications, and beyond. With increasing demand for ML specialists, job seekers who continually update their knowledge and skills hold a significant advantage. In this article, we've curated ten essential books every machine learning professional or aspiring ML engineer in the UK should read. Covering foundational theory, practical implementations, advanced techniques, and industry trends, these resources will equip you to excel in your machine learning career.