12 of 12 Contract Machine Learning Jobs in the City of London

engaging closely with both technical and non-technical stakeholders. Delivery is supported by a strong technical assurance and review culture, encouraging challenge, learning and high standards. You will work within security, compliance and governance constraints where quality and judgement matter as much as pace. What You'll Be Doing … learning models Experience evaluating models through quantitative evidence and structured experimentation Strong software engineering practices, producing readable, testable and maintainable code Experience integrating ML solutions into production systems and workflows Feels confident working in secure, regulated or high-assurance environments In Return You'll work on genuinely challenging machine ...

Group Functions, Retail and Investment Banking. On behalf of this organisation, AMS are looking for a Business/Data Analyst with strong experience in machine learning system implementation, for a 6 month contract (with potential for extension) based in the London office (hybrid model, 2 days a week … Business/Data Analyst will support the implementation of our client's transaction monitoring system from a legacy rules-based environment to a Machine Learning-driven AML platform. This role sits within the Product team and will play a key role in defining requirements, supporting model development ...

will be designing and building AI-enabled software systems that support complex operational environments. The role will involve developing scalable backend services, integrating machine learning models into production systems, and contributing to the architecture of secure, cloud-native platforms. This is a hands-on engineering role suited … NEED THE AI SOFTWARE ENGINEER TO HAVE. Active UKSV DV clearance Strong software engineering background with Python Experience building and deploying AI/machine learning applications Knowledge of LLMs, NLP, or generative AI frameworks Experience with AWS or Azure Familiarity with Docker and Kubernetes Experience working in secure ...

high-trust, delivery-focused environment where technical quality, judgement and real-world impact are valued. The team operates collaboratively, sharing knowledge and learning through delivery rather than theory alone. You will be trusted to manage your own work, engage directly with customers and stakeholders, and take responsibility for outcomes. … engagement - Work directly with users and customers to understand real-world needs and translate them into well-defined AI problems - Apply modern AI and machine learning techniques using strong Python engineering skills - Build solutions that can operate in secure, constrained or offline environments without reliance on external services ...

through their full lifecycle, from deployment to live operation and support - Ensure systems are supportable, secure, monitored and reliable in production - Configure and operate machine learning workloads in production, focusing on running models rather than training - Monitor system performance, identify issues and troubleshoot problems in live environments - Work … infrastructure-as-code tools such as Terraform - Confidence taking responsibility for live systems and outcomes MLOps experience is highly attractive, particularly operating AI or machine learning models in production. The focus is on operating models, not training them. In Return You'll work on platforms that support ...

working within Agile delivery environments. Desirable Experience Databricks certifications. Kafka or Structured Streaming. CI/CD and DevOps practices. Docker and Kubernetes. Exposure to Machine Learning pipelines. Experience within Financial Services or other highly regulated environments. About You You'll be an experienced Data Engineer or Technical Lead ...

Data Engineer for a 12-month contract. In this role, you will help design and optimize high-throughput data frameworks that feed advanced machine learning models and drive high-performance user applications. This role offers a unique chance to work across a modern, full-stack cloud data environment … BigQuery/Snowflake Orchestration: Airflow Backend: Python, SQL, Shell Languages: Scala/Java DevOps: Terraform, Docker, Kubernetes Observability: Monte Carlo BI: Looker AI/ML: MLOps London | 12 Months Contract |£400 a day Inside IR35 If you want to work in an organisation where engineering quality is deeply respected, this ...

product instinct; senior leadership. Core Competencies: Strong AI, cybersecurity , and software engineering experience. Experience with LLM s and frontier AI models rather than traditional machine learning alone. Deep technical expertise and ability to actively contribute to engineering work. Exploit development/offensive security experience. Experience helping organisations strengthen ...

stakeholders and translating complex tech into real-world impact What we're looking for: Strong experience across software engineering, data platforms, and AI/ML Proven leadership in DevOps, cloud, and modern engineering practices Experience delivering in innovative or regulated environments Ability to operate in ambiguity and influence at senior ...

engaging closely with both technical and non-technical stakeholders. Delivery is supported by a strong technical assurance and review culture, encouraging challenge, learning and high standards. You will work within security, compliance and governance constraints where quality and judgement matter as much click apply for full job details ...

AMS is a global workforce solutions partner committed to creating inclusive, dynamic, and future-ready workplaces. We help organisations adapt, grow, and thrive in an ever-evolving world by building, shaping, and optimising diverse talent ...

platform usability and operational excellence matter. The work sits at the intersection of platform engineering, DevOps and MLOps, with close collaboration across data science, ML engineering, software engineering and architecture. The role requires comfort working 'in the weeds' - understanding how platforms behave under real workloads, and designing guardrails that balance … experimentation (including notebooks), packaging, deployment and versioning - Enable scalable inference and LLM-based workloads, including serving and optimisation considerations - Work with data scientists and ML engineers to ensure the platform is usable, well documented and fit for purpose - Own platform operability, reliability, security and supportability in live production environments - Troubleshoot ...