112 Image Analysis jobs in London

A leading global hedge fund is looking to speak with Machine Learning researchers from any industry background who might be interested in applying their expertise to the trading domain. You'll be working alongside experienced portfolio management/trading teams to research and implement machine learning strategies to search for alphas in large, unstructured data sets.

Requirements:

-PhD in Machine Learning or related discipline.

-3+ years industry experience applying innovative ML research to real-world problems.

-Experience with large-scale data sets and unstructured data sources.

-Interest in quantitative trading.

-Hands-on coding experience in Python and/or compiled languages.

We are seeking a highly skilled Machine Learning Engineer to join our team on a contract basis. You will be responsible for designing, building, and deploying machine learning models into production, working closely with data scientists, software engineers, and product teams to deliver scalable AI solutions. This is an excellent opportunity for someone who thrives in fast-paced environments and enjoys solving complex problems with real-world impact.

Key Responsibilities

• Develop, train, and optimize machine learning models for production use.
• Collaborate with data scientists to turn research prototypes into production-grade solutions.
• Build robust data pipelines and feature engineering workflows.
• Deploy ML solutions into cloud environments (AWS, GCP, or Azure).
• Implement monitoring, testing, and model performance evaluation frameworks.
• Work with engineering teams to ensure seamless integration of ML models into products.
• Contribute to improving infrastructure, tooling, and best practices for ML development and deployment.

Skills & Experience

Essential:

• Strong programming skills in Python (and frameworks such as PyTorch, TensorFlow, or Scikit-learn).
• Proven experience in developing and deploying machine learning models in production.
• Solid understanding of data structures, algorithms, and software engineering principles.
• Experience with ML pipelines and orchestration tools (e.g., Airflow, Kubeflow, MLflow).
• Proficiency in working with cloud services (AWS, GCP, or Azure).
• Strong understanding of CI/CD, containerisation (Docker), and orchestration (Kubernetes).
• Excellent problem-solving skills and ability to work independently in a fast-paced environment.

Desirable:

• Experience with NLP, computer vision, or time-series forecasting.
• Familiarity with distributed computing frameworks (Spark, Ray).
• Experience with MLOps and model governance practices.
• Previous contract experience in a similar ML engineering role.

Contract Details

• Duration: 6–12 months (extension possible)
• Location: London (Hybrid working model)
• Day Rate: Competitive, depending on experience

Lead ML Engineer - Onsite 5 days a week - London

Happy to look at European relocators

An Edtech Start-up in London are building something transformative in the education space using cutting-edge machine learning.

We're looking for a Lead ML Engineer to take ownership of the machine learning strategy, build out the team, and help shape the future of AI in education.

Responsibilities:

• Build and lead a new ML team from the ground up.
• Define the tech stack for data pipelines and ML models.
• Develop generative models using diverse datasets (text, audio, video, test results).
• Design and deploy data integration and analysis pipelines.
• Collaborate with engineers and product managers to bring ML features to life.
• Create innovative language assessments and predictive models.
• Optimize models for performance, scalability, and accuracy.

Qualifications:

• Deep knowledge of neural networks (CNNs, RNNs, LSTMs, Transformers).
• Strong experience with data tools (Pandas, NumPy, Apache Spark).
• Solid understanding of NLP algorithms.
• Experience integrating ML models via RESTful APIs.
• Familiarity with CI/CD pipelines and deployment automation.
• Strategic thinking around architecture and trade-offs.

If interested please get in touch ASAP!

Please note this Role is based in London, local candidates only!

Solvo.ai is redefining global container shipping with AI. We build machine learning systems that power intelligent, sustainable, and profitable decision-making for one of the world’s most complex industries. Nothing we do is hypothetical. Everything we do has a measurable impact. 

Our combined experience of over 100 years in logistics, artificial intelligence and scaling startups allows us to innovate boundlessly, constantly push the frontiers of what’s possible, and generate revolutionary tools to deliver business impact to our customers. 

We stand proudly, not just for what we achieve, but for how we achieve it - creating trust through professionalism, integrity, and transparency.

The role:

We are looking for an exceptional Machine Learning Engineer (MLE) to join our team and accelerate the next generation of Solvo’s AI products. This is a hands-on role at the intersection of research and production, where your work will ensure our customers get maximum value out of our solutions.

The ideal candidate for this role will get stuck in across the organisation, moving naturally from intricate data analysis, through detailed ML considerations and onto the broader business context. 

You will have the freedom to propose, research and implement innovative new ideas to improve our system. 

If you want to apply cutting-edge machine learning to a trillion-dollar industry, and you’re motivated by seeing your work have immediate business impact, we’d love to hear from you.

Your responsibilities

• Innovate on Solvo’s modelling and decision making solution.
• Create value for customers through application of ML principles and best practice.
• Strive for high quality and robust outcomes.
• Continuously ensure we are using the most appropriate ML modelling techniques for customer projects and our product offerings.
• Design and develop production-grade software, ensuring scalability and performance.
• Collaborate closely with scientists and engineers in an agile team environment.
• Facilitate understanding of our AI solutions internally and externally.
• Continuously develop your own AI/ML and engineering skills.

Essential skills and experience

• Academic or industrial research experience in machine learning, especially probabilistic models and Bayesian statistics.
• Proficiency in designing and programming advanced ML algorithms.
• Ability to apply state-of-the-art research to real-world problems.
• Proficiency in operating and evolving advanced ML systems in a production environment.
• Strong communication skills with the ability to convey complex ideas to both technical and non-technical audiences.
• Advanced degree (PhD/MSc) in a relevant field (e.g., Computer Science, Statistics, Applied Mathematics).
• Experience working in an agile team environment.

Desired qualifications, skills and experience

• PhD degree in a relevant field.
• Good working knowledge of optimisation (linear programming).
• Strong experience with Python and standard ML libraries.
• Familiarity with cloud computing platforms (e.g., AWS, Google Cloud, Azure).

Equal employment opportunity

Solvo.ai is an equal opportunity employer and we value diversity. We do not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Benefits

1. A competitive compensation package including equity
2. Career growth opportunities on a personal and professional level
3. Be part of a very talented, collaborative team that continuously strives for innovative solutions
4. A friendly work environment where you are expected to challenge and be challenged every single day
5. 25 days paid holiday

Job type: full-time; permanent contract; On-site (hybrid)Location

London, United Kingdom

Machine Learning Engineer | Generative AI | AWS | End-to-End ML Solutions

Location: London-based | Hybrid

Please note: Sponsorship is not offered for this position

We’re working with a leading organisation on a mission to become one of the most insight-driven businesses in its sector, placing machine learning and generative AI at the core of customer experiences, operational optimisation, and strategic decision-making.

This is a fantastic opportunity for a skilled Machine Learning Engineer to build and deploy scalable, production-level ML solutions, working closely with Data Scientists and cross-functional teams to drive measurable business impact.

You’ll play a pivotal role in integrating machine learning models into end-to-end pipelines, supporting strategic initiatives such as customer engagement, automated insights, and decision-support tooling. You’ll also contribute to shaping the frameworks, infrastructure, and shared tooling that enable safe, responsible, and efficient AI experimentation and deployment.

If you’re passionate about problem-solving, applying ML to real-world challenges, and bringing ideas to life in production environments, this role is a great fit.

What You’ll Be Doing

Machine Learning Engineering

• Build, deploy, and maintain ML models as services, streaming applications, or batch jobs across real-time and offline platforms.
• Develop scalable model APIs with strong CI/CD and observability practices.
• Implement model testing, monitoring, and rollback capabilities in production environments.
• Collaborate with Data Scientists to translate prototypes into reliable, maintainable ML applications.
• Identify opportunities to develop new ML solutions in partnership with Data Science teams.

Platform & Tooling

• Automate and standardise ML infrastructure using Docker, Kubernetes, and Terraform.
• Support and develop monitoring dashboards for key ML and AI services.
• Ensure cloud-native, secure, and cost-efficient deployments in AWS environments.
• Contribute to the development of shared platforms and tooling that enable model deployment and experimentation.

Compliance

• Adhere to governance, risk, and compliance obligations relevant to the role.
• Identify and escalate non-compliance issues when necessary.
• Proactively challenge processes that may impact compliance standards.
• Complete all mandatory compliance training and engage with compliance teams for clarification when needed.

What You’ll Bring

• 3–5 years of experience in machine learning engineering and data science.
• Advanced degree (PhD or Master’s) in a numerate discipline.
• Excellent programming skills in Java and Python for production systems.
• Strong foundations in machine learning and data science.
• Experience deploying ML models as APIs, batch jobs, or streaming services (e.g., Kafka Streams).
• Proficiency in containerised application deployment with Kubernetes.
• Demonstrated experience building ML solutions from concept to delivery.
• Strong cloud engineering skills (AWS preferred; Terraform or CloudFormation a plus).
• Excellent communication and collaboration skills.
• Up-to-date knowledge of modern ML and AI developments.

Why Join

This is a chance to work on impactful machine learning use cases that shape the future of customer experiences and business operations. You’ll be part of a collaborative environment where innovation is encouraged, and you’ll have the autonomy to influence tooling, frameworks, and production ML strategy.

Please note: Sponsorship is not offered for this position. Candidates must have the existing right to work in the relevant location.

Machine learning Quantitative Engineer

London - Hybrid working

Rate - £1,200

Key Responsibilities

• Research, design, and implement machine learning and quantitative models for pricing, trading signals, and risk management across Fixed Income products (rates, credit, FX, mortgages).
• Apply advanced statistical learning methods (time-series, NLP, deep learning, reinforcement learning, graph-based models) to large-scale, high-frequency, and alternative datasets.
• Engineer robust data pipelines and real-time model deployment frameworks to support production trading environments.
• Collaborate with traders, quants, and technologists to prototype and scale strategies from research to execution.
• Conduct rigorous backtesting, performance analysis, and explainability assessments of machine learning models.
• Contribute to the development of quantitative libraries and shared research infrastructure.

Qualifications & Skills

Essential:

• Strong expertise in machine learning, statistical modelling, and numerical methods with practical applications.
• Proficiency in Python (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow) and experience with C++ or Java for high-performance model integration.
• Solid understanding of Fixed Income products, yield curve modelling, and financial mathematics.
• Experience building production-level ML systems in low-latency or large-scale environments.
• Strong communication skills with the ability to interact effectively with both technical and trading stakeholders.

Desirable:

• Previous front-office or systematic trading desk experience.
• Familiarity with modern MLOps (Docker, Kubernetes, MLflow, Airflow) and distributed computing (Spark, Ray).
• Experience with alpha signal generation, regime detection, or portfolio optimization.
• Exposure to alternative/ESG datasets, macroeconomic indicators, and sentiment analysis.

An AI-driven start-up, backed by $20M in Series A funding, is looking for its first Machine Learning Engineer to help scale their product and infrastructure. The platform transforms educational content into smart, personalised learning tools - and is already seeing rapid user growth and strong traction in the market.

This is a unique opportunity to join early, influence the technical roadmap, and work directly with experienced founders and a senior engineering team.

What you’ll be doing:

• Designing, building and deploying ML-powered features across a production platform
• Working across Python and TypeScript , integrating models into scalable, real-time systems
• Fine-tuning and training NLP models using techniques like transformers
• Driving the machine learning strategy and building best practices from the ground up
• Collaborating closely with product, engineering, and leadership

What we’re looking for:

• Strong commercial experience building and deploying ML models in production
• Proficiency in Python and familiarity with TypeScript/JavaScript
• Experience with NLP or recommendation systems is a bonus
• Excited by start-ups: product-minded, hands-on, and motivated by impact

What’s on offer:

• £100,000 - £120,000 salary + meaningful equity
• 4 days/week in a modern London office near Liverpool St
• Greenfield ML ownership with direct access to founding team
• A chance to shape the future of an AI product already loved by users