Applied AIML Lead & Python & Data Science Engineering

JPMorgan Chase & Co.; Glasgow; On-site; GBP 60,000 - 80,000; Full time

Job summary

A global financial institution in Scotland is seeking an Applied AIML Engineer to develop and implement cutting-edge machine learning models and generative AI applications. This role emphasizes collaboration, scalability, and technical excellence in a dynamic environment. Expertise in Python, cloud platforms, and solid understanding of AI tools are essential. Join us to drive innovation while mentoring junior engineers in best practices.

Qualifications

• Proven experience deploying AI/ML applications in a production environment.
• Strong emphasis on writing comprehensive test cases for code reliability.
• Expertise in cloud storage and familiarity with generative AI models.

Responsibilities

• Co-develop and implement LLM-based machine learning models.
• Design and deploy generative AI applications.
• Analyze large datasets for actionable insights.

Skills

API design and engineering

Python programming

MLOps practices

Data preprocessing

Cloud platforms (AWS)

Generative AI models

Education

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

Tools

API frameworks (Quart, Flask, FastAPI)

Index & Vector DBs (Opensearch/ElasticSearch)

AI frameworks (TensorFlow, PyTorch)

Containerization technologies (Docker, Kubernetes)

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.