Build and deploy practical machine learning, deep learning, and generative AI solutions. Design and evaluate experiments, work with large language models and AI agents, write production-quality code, optimize model performance, and collaborate with product and engineering teams to deliver scalable AI systems.
We’re looking for an Applied AI Scientist with strong machine learning experience to join our AI Technologies team.
In this role, you’ll help build practical machine learning and generative AI solutions that can move from experimentation into production. You’ll work closely with product owners, data engineers, software engineers, and other ML practitioners to design, test, improve, and deploy AI/ML capabilities at scale.
This is a hands-on role for someone who enjoys solving technical problems, writing code, experimenting with new approaches, and turning ideas into reliable systems.
Job Responsibilities:
- Define problems, success measures, and technical approaches with product and engineering teams.
- Design experiments, establish baselines, and benchmark models and agent systems. Investigate failures and use the results to guide improvements.
- Own Python development from experimental prototypes to tested production code, working with engineers on deployment and monitoring.
- Make and explain trade-offs between model quality, reliability, latency, and cost.
- Lead technical design reviews and mentor other ML practitioners.
- Work with engineering and control teams to meet data, model governance, and security requirements.
Required Qualifications, Capabilities, and Skills:
- At least five years of applied ML experience, including leading complex technical work and taking models into production.
- Strong knowledge of machine learning and deep learning, with experience selecting methods, designing experiments, and evaluating results.
- Strong Python skills and experience writing tested, maintainable software.
- Hands-on experience building and evaluating LLM-based systems, including retrieval, tool use, or agent orchestration.
- The ability to turn unclear requirements into testable problems, drive work independently, and explain technical decisions clearly.
- A STEM degree or equivalent practical experience.
Preferred Qualifications, Capabilities, and Skills:
- Experience fine-tuning models or optimizing inference, using frameworks such as PyTorch or TensorFlow.
- Experience deploying and operating ML systems on cloud platforms, particularly AWS services such as SageMaker or EKS.
- Programming experience in Java, C/C++, or another production language.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
JPMorganChase London, England Office
25 Bank Street, Canary Wharf, London, United Kingdom, E14 5JP
Similar Jobs
Financial Services
Lead design, build, and deploy enterprise-scale AI solutions and multi-agent systems. Drive model lifecycle, monitoring, retraining, evaluation frameworks, semantic knowledge systems, and integration into operational workflows while communicating results to senior leadership.
Top Skills:
A/B TestingAdkAdvanced AnalyticsAi/MlAutomated Information RetrievalCloudData MeshDrift MonitoringKnowledge BaseLanggraphModel RetrainingMulti-Agent SystemsOrchestration FrameworksSemantic Search
Artificial Intelligence • Cloud • Computer Vision • Hardware • Internet of Things • Software
Provides onsite and remote technical support for employees, manages helpdesk tickets, and handles onboarding, laptop provisioning, system access, hardware recovery, and asset management. Maintains office endpoints, printers, and conference room equipment while supporting cloud infrastructure access, networking, security audits, SaaS rollouts, scripting, and IT projects. Documents procedures, manages escalations, and improves support operations. The position requires five days per week onsite in London, with occasional urgent after-hours support.
Top Skills:
Apple MacosCloud InfrastructureGoogle Workspace (G Suite)iOSNetworkingOktaSaaSServicenowSlackZendeskZoom
.png)
eCommerce • Fintech • Hardware • Payments • Software • Financial Services
As an Enterprise Account Executive, you will manage high-value deals throughout the sales process, collaborate with technical teams, and represent the company to executive clients, all while developing relationships and strategies to drive enterprise sales success.
Top Skills:
Api IntegrationsFintechSaaS
What you need to know about the London Tech Scene
London isn't just a hub for established businesses; it's also a nursery for innovation. Boasting one of the most recognized fintech ecosystems in Europe, attracting billions in investments each year, London's success has made it a go-to destination for startups looking to make their mark. Top U.K. companies like Hoptin, Moneybox and Marshmallow have already made the city their base — yet fintech is just the beginning. From healthtech to renewable energy to cybersecurity and beyond, the city's startups are breaking new ground across a range of industries.
