AI Jobs in London

Find top AI jobs in London across machine learning, generative AI, and data roles. All opportunities are curated and updated hourly from companies hiring nationwide.

Check out 28 new AI opportunities posted on The Homebase

Freelance Software Developer (Kotlin) - AI Trainer

New
Top rated
Mindrift
Part-time
Full-time
Posted

As an AI Tutor in Coding specializing in Kotlin development, the responsibilities include designing high-quality technical content, examples, and explanations demonstrating best practices in Kotlin development; collaborating with engineers to ensure accuracy and consistency across code samples, tutorials, and developer guides; exploring modern Kotlin frameworks and tools to create practical, real-world examples for learning and testing; and continuously refining content based on feedback, emerging patterns, and advances in the Kotlin ecosystem. The role also involves contributing to projects aligned with skills by creating training prompts and refining model responses to help shape the future of AI while ensuring technology benefits everyone.

$80 / hour
Undisclosed
HOUR

(USD)

United States
Maybe global
Remote

AI / ML Solutions Engineer

New
Top rated
Anyscale
Full-time
Full-time
Posted

The AI / ML Solutions Engineer at Anyscale is responsible for designing, implementing, and scaling machine learning and AI workloads using Ray and Anyscale directly with customers. This includes implementing production AI / ML workloads such as distributed model training, scalable inference and serving, and data preprocessing and feature pipelines. The role involves working hands-on with customer codebases to refactor or adapt existing workloads to Ray. The engineer advises customers on ML system architecture including application design for distributed execution, resource management and scaling strategies, and reliability, fault tolerance, and performance tuning. They guide customers through architectural and operational changes needed to adopt Ray and Anyscale effectively. Additionally, the engineer partners with customer MLE and MLOps teams to integrate Ray into existing platforms and workflows, supports CI/CD, monitoring, retraining, and operational best practices, and helps customers transition from experimentation to production-grade ML systems. They also enable customer teams through working sessions, design reviews, training delivery, and hands-on guidance, contribute feedback to product, engineering, and education teams, and help develop reference architectures, examples, and best practices based on real customer use cases.

Undisclosed

()

Maybe global
Remote

Senior Software Engineer, Applied AI

New
Top rated
Lumi AI
Full-time
Full-time
Posted

As a Software Engineer working on AI systems, responsibilities include playing a foundational role in research, experimentation, and rapid improvement of AI systems to build a capable, reliable AI automation platform used worldwide in mission critical production environments. Tasks involve designing experiments and testing ideas to optimize key internal AI benchmarks, designing and improving evaluation frameworks to accelerate experimentation speed and direction, training, fine-tuning, and optimizing machine learning models, performing rigorous evaluation and testing for model accuracy, generalization, and performance, collaborating and contributing to core product development to enhance platform capabilities, and setting up observability and monitoring systems to safety check model behavior in critical settings.

$170,000 – $250,000
Undisclosed
YEAR

(USD)

United States
Maybe global
Onsite

Lead Machine Learning Engineer

New
Top rated
Fyxer
Full-time
Full-time
Posted

The Lead Machine Learning Engineer will own the development and improvement of the system predicting the next action salespeople should take to advance their relationships. Responsibilities include selecting the best model architecture and approach, involving a mixture of LLM steps and traditional ML models, picking evaluation metrics, designing systems to analyze models in production to identify areas for improvement, and identifying when to use the human data team for training or validation datasets. The engineer will read relevant research to find the best approach for their use case and, in partnership with the CTO, define how machine learning works with product engineering, model operations, and human data teams and how the team should develop moving forward.

£200,000 – £200,000
Undisclosed
YEAR

(GBP)

London, United Kingdom
Maybe global
Hybrid

Lead Machine Learning Engineer

New
Top rated
Faculty
Full-time
Full-time
Posted

Set the technical direction for complex machine learning projects, balancing trade-offs and guiding team priorities. Design, implement, and maintain reliable, scalable ML and software systems while justifying key architectural decisions. Define project problems, develop roadmaps, and oversee delivery across multiple workstreams in often ill-defined, high-risk environments. Drive the development of shared resources and libraries across the organisation and guide other engineers in contributing to them. Lead hiring processes, make informed selection decisions, and mentor multiple individuals to foster team growth. Proactively develop and execute recommendations for adopting new technologies and changing ways of working to stay competitive. Act as a technical expert and coach for customers, accurately estimate large workstreams, and defend rationale to stakeholders.

Undisclosed

()

London, United Kingdom
Maybe global
Hybrid

Software Engineer, macOS Core Product - Intl, Non-USA

New
Top rated
Speechify
Full-time
Full-time
Posted

Work alongside machine learning researchers, engineers, and product managers to bring AI Voices to customers for a diverse range of use cases. Deploy and operate the core ML inference workloads for the AI Voices serving pipeline. Introduce new techniques, tools, and architecture that improve the performance, latency, throughput, and efficiency of deployed models. Build tools to provide visibility into bottlenecks and sources of instability and design and implement solutions to address the highest priority issues.

$140,000 – $200,000
Undisclosed
YEAR

(USD)

United States
Maybe global
Remote

Software Engineer, macOS Core Product - Virginia Beach, USA

New
Top rated
Speechify
Full-time
Full-time
Posted

Work alongside machine learning researchers, engineers, and product managers to bring AI Voices to customers for diverse use cases. Deploy and operate the core machine learning inference workloads for the AI Voices serving pipeline. Introduce new techniques, tools, and architecture to improve performance, latency, throughput, and efficiency of deployed models. Build tools to identify bottlenecks and sources of instability, then design and implement solutions addressing the highest priority issues.

$140,000 – $200,000
Undisclosed
YEAR

(USD)

Maybe global
Remote

Software Engineer, macOS Core Product - Rialto, USA

New
Top rated
Speechify
Full-time
Full-time
Posted

Work alongside machine learning researchers, engineers, and product managers to bring AI Voices to their customers for diverse use cases. Deploy and operate the core ML inference workloads for the AI Voices serving pipeline. Introduce new techniques, tools, and architecture to improve the performance, latency, throughput, and efficiency of deployed models. Build tools to gain visibility into bottlenecks and sources of instability and design and implement solutions to address the highest priority issues.

$140,000 – $200,000
Undisclosed
YEAR

(USD)

Maybe global
Remote

Software Engineer, macOS Core Product - Waco, USA

New
Top rated
Speechify
Full-time
Full-time
Posted

Work alongside machine learning researchers, engineers, and product managers to bring AI Voices to customers for a diverse range of use cases. Deploy and operate the core ML inference workloads for the AI Voices serving pipeline. Introduce new techniques, tools, and architecture to improve the performance, latency, throughput, and efficiency of deployed models. Build tools to provide visibility into bottlenecks and sources of instability, and design and implement solutions to address the highest priority issues.

$140,000 – $200,000
Undisclosed
YEAR

(USD)

Maybe global
Remote

Software Engineer, macOS Core Product - South Bend, USA

New
Top rated
Speechify
Full-time
Full-time
Posted

Work alongside machine learning researchers, engineers, and product managers to bring AI Voices to customers for a diverse range of use cases. Deploy and operate the core ML inference workloads for AI Voices serving pipeline. Introduce new techniques, tools, and architecture that improve the performance, latency, throughput, and efficiency of deployed models. Build tools to provide visibility into bottlenecks and sources of instability and then design and implement solutions to address the highest priority issues.

$140,000 – $200,000
Undisclosed
YEAR

(USD)

Maybe global
Remote

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[{"question":"What types of AI jobs are available in London?","answer":"London offers a diverse AI job market with 2,146 permanent positions in early 2026. Common roles include AI Engineers (designing and deploying smart systems), Data Scientists (working with large datasets), Machine Learning Specialists, and Chatbot Developers. Emerging positions gaining traction include AI Operations Engineers, AI Automation Leads, AI Agent Orchestrators, and AI Product Owners. The London market particularly values expertise in large language models, with most AI positions now involving LLM workflows. Ethics and compliance specialists are also increasingly sought after as companies prioritize responsible AI development."},{"question":"Are there remote or hybrid AI jobs available in London?","answer":"Yes, remote AI jobs form a substantial segment of London's market with 2,758 permanent work-from-home vacancies across the UK. These remote positions average £67,500 in salary, slightly below the London on-site average of £80,000. While most London AI roles still favor on-site or hybrid arrangements, the remote option remains viable for professionals seeking flexibility. Companies typically offer remote work for roles involving independent development, model training, and data analysis. Hybrid arrangements have become increasingly common, especially for collaborative positions like AI Product Managers or teams working on complex deployments requiring occasional in-person coordination."},{"question":"What skills are most in demand for AI jobs in London?","answer":"London employers prioritize Python proficiency alongside experience with machine learning frameworks like TensorFlow, PyTorch, and scikit-learn. Natural language processing has become essential, particularly with the rise of LLM implementations. Data engineering capabilities, cloud computing expertise (especially AWS and Azure), and API development round out the technical requirements. Skills are evolving 66% faster than in other fields, with prompt engineering now commanding significant wage premiums. Beyond technical abilities, AI ethics understanding, business domain knowledge, and the ability to explain complex models to stakeholders have become increasingly valuable as AI systems touch more critical business functions."},{"question":"What is the salary range for AI jobs in London?","answer":"AI roles in London command an impressive average salary of £80,000, substantially higher than the UK average of £60,000 (excluding London). Compensation varies significantly based on specialization, with AI Engineers earning £65,000-£120,000+ and Data Scientists commanding £60,000-£125,000+. AI Product Managers typically see £70,000-£120,000+, while Ethics & Compliance Specialists range from £50,000-£100,000+. Factors influencing salary include expertise with cutting-edge technologies (particularly LLMs), industry sector (finance and healthcare typically pay premium rates), years of experience, and demonstrated project success. Workers with AI skills consistently earn wage premiums across all industries."},{"question":"What experience levels are companies hiring for AI jobs in London?","answer":"London companies are hiring across experience levels, but the entry-level landscape is tightening. Even junior positions now expect portfolios, GitHub repositories, Kaggle competition experience, or open-source contributions. Mid-level roles typically require 3-5 years of practical AI implementation experience, while senior positions demand 7+ years with demonstrable business impact. Companies increasingly value practical experience over formal education alone, though advanced degrees still provide an advantage. The shift toward requiring project evidence reflects the maturing market where employers seek proven capability rather than potential. For specialists in emerging areas like generative AI, demonstrating self-directed learning can sometimes offset years of formal experience."},{"question":"How often are new AI jobs posted in London?","answer":"London sees approximately 170 new AI job postings monthly, based on the most recent six-month data showing 2,146 permanent AI vacancies. This represents about 23% of all UK AI roles, making London the fourth-largest AI hiring hub in the country. The posting frequency has increased by 31% year-on-year compared to 2025, significantly outpacing general job market growth. Postings typically surge in January and September, aligning with annual budget approvals and project kickoffs. Despite the broader UK job market contraction, AI positions remain resilient as companies treat AI as strategic investments rather than optional hiring, particularly for roles involving LLMs."},{"question":"What is the difference between The Homebase and other job boards?","answer":"The Homebase specializes exclusively in AI jobs, unlike general job boards where AI positions represent only a fraction of listings. This specialization allows for more nuanced filtering by AI subspecialties like machine learning, computer vision, or NLP. Candidates benefit from curated listings focusing on genuine AI roles rather than positions merely mentioning AI as a buzzword. The platform attracts employers specifically seeking AI talent, resulting in higher-quality matches. While general job boards might offer broader reach, they often lack the technical specificity needed for AI career progression. The Homebase also provides AI-specific resources, salary insights, and skill requirement trends not found on general platforms."}]