Applied AIML Lead & Python & Data Science Engineering

J.P. Morgan; Glasgow; On-site; GBP 60,000 - 85,000; Full time

Job summary

A leading financial institution seeks an Applied AIML Engineer to leverage AI technologies for operational excellence. The role involves developing LLM-based models and generative AI applications, optimizing processes while collaborating with stakeholders. The ideal candidate should have a strong educational background in computer science or related fields, exhibit excellent skills in Python programming, and possess experience in deploying AI/ML solutions in production environments. This is an exciting opportunity to make impactful contributions in a top-tier company.

Qualifications

• Master’s or Bachelor’s degree with engineering focus.
• Extensive experience deploying AI/ML applications.
• Expertise with Index & Vector DBs like ElasticSearch.

Responsibilities

• Co-Develop LLM-based machine learning models.
• Design generative AI applications to optimize processes.
• Collaborate to translate business needs into technical solutions.

Skills

API design

Python programming

Machine Learning

Data Science

MLOps practices

Education

Master’s or Bachelor’s in Computer Science, Data Science, Machine Learning, or related field

Tools

AWS (SageMaker, Bedrock)

ElasticSearch

Docker

TensorFlow

Job description

If you are looking for a game-changing career, working for one of the world's leading financial institutions, you’ve come to the right place.

As an Applied AIML Engineer, you provide expertise and engineering excellence as an integral part of an agile team to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Leverage your advanced technical capabilities and collaborate with colleagues across the organization to drive best-in‑class outcomes across various technologies to support one or more of the firm’s portfolios.

Job responsibilities

• Co-Develop and implement LLM-based, machine learning models and algorithms to solve complex operational challenges.
• Design and deploy generative AI applications to automate and optimize business processes.
• Collaborate with stakeholders & Data Scientists to understand business needs and translate them into technical solutions.
• Analyze large datasets to extract actionable insights and drive data‑driven decision‑making.
• Ensure the scalability and reliability of AI/ML solutions in a production environment.
• Stay up-to-date with the latest advancements in AI/ML technologies & LLMs and integrate them into our operations.
• Mentor and guide junior team members in coding & SDLC standards, AI/ML best practices and methodologies.

Required qualifications, capabilities, and skills

• Master’s or Bachelors in Computer Science, Data Science, Machine Learning, or a related field, with a focus on engineering.
• Excellent API design and engineering experience with proven usage of API python frameworks Quart, Flask or FastAPI
• Proficiency in Python & async programming, with a strong emphasis on writing comprehensive test cases using testing frameworks such as pytest to ensure code quality and reliability
• Expertise with Index & Vector DBs such as Opensearch./ElasticSearch
• Extensive experience in deploying AI/ML applications in a production environment, with skills in deploying models on AWS platforms such as SageMaker or Bedrock.
• Champion of MLOps practices, encompassing the full cycle from design, experimentation, deployment, to monitoring and maintenance of machine learning models.
• Experience with generative AI models, including GANs, VAEs, or transformers. Experience with Diffusion models is a plus.
• Solid understanding of data preprocessing, prompt engineering, feature engineering, and model evaluation techniques.
• Proficiency in AI coding tools and editors such as Cursor, Windsurf or CoPilot
• Familiarity in machine learning frameworks such as TensorFlow, PyTorch, PyTorch Lightning, or Scikit-learn.
• Familiarity with cloud platforms (AWS) and containerization technologies (Docker, Kubernetes, Amazon EKS, ECS).

Preferred qualifications, capabilities, and skills

• Expertise in cloud storage such as RDS and S3
• Excellent problem-solving skills and the ability to work independently and collaboratively.
• Strong communication skills to effectively convey complex technical concepts to non-technical stakeholders.
• Proven experience in leading projects and teams, with a track record of successful project delivery.