Lead AI/ML Ops Engineer

Testing Site - JPMC; Dublin; On-site; EUR 70,000 - 110,000; Full time

Job summary

JPMorgan Chase Dublin is seeking a Machine Learning Engineer to design, implement, and deploy models that align with global standards and governance. You will collaborate with ML scientists, data scientists, software engineers, and product teams to scale impactful AI solutions across the firm.

In this role you will deploy models to production, fine-tune for performance, monitor accuracy, and work across platforms such as AWS and Databricks to deliver robust data-driven capabilities for our 300k+

Qualifications

• Proficiency in Python and software engineering basics.
• Experience with ML libraries such as PyTorch, TensorFlow, or Scikit-learn.
• Data preprocessing, feature engineering, and building data pipelines.
• Familiar with distributed data processing (Spark/PySpark) and model deployment.
• Experience deploying ML models on AWS or similar platforms.

Responsibilities

• Design and implement machine learning models in collaboration with ML scientists, ensuring alignment with global technology standards and governance.
• Deploy and scale models to production environments, ensuring robustness and reliability.
• Fine-tune models for optimal performance and efficiency, addressing issues that arise.
• Collaborate with data scientists, software engineers, and product teams to integrate ML solutions into existing systems.
• Continuously monitor model performance and adjust to maintain accuracy and efficiency.

Skills

Python proficiency

Software engineering fundamentals

Data preprocessing & feature eng.

Building data pipelines

Model deployment & monitoring

Tools

PyTorch

MLflow

TensorFlow

Scikit-learn

Apache Spark / PySpark

AWS Cloud Platform

Databricks

Job description

Elevate your career by working with new AI and machine learning technologies, focusing on delivering impactful solutions. We provide opportunities to help you reach your full potential, offering the support you need to achieve your career goals. The Employee Platforms technology team is excited to invest in Dublin, establishing an engineering hub focused on the growth and application of innovative technologies to enhance the experience of our 300k+ employees.

As a Machine Learning Engineer within the JPMorgan Chase team, you will design, implement, and deploy machine learning models that adhere to our global technology standards and firm governance requirements. Collaborate closely with machine learning scientists, data scientists, software engineers, and product teams to integrate and scale machine learning solutions that promote significant business impact. Your responsibilities include designing and implementing machine learning models, deploying and scaling models to production environments, fine-tuning models for optimal performance, and continuously monitoring model performance.

J.P. Morgan Dublin thrives as a collaborative, tight-knit community, passionately driven by innovation, where curiosity fuels the relentless pursuit of groundbreaking ideas. The culture is centred around exploring new frontiers together by fostering an environment that encourages growth, creativity and forward-thinking.

Job Responsibilities:

• Design and implement machine learning models in collaboration with machine learning scientists, ensuring alignment with global technology standards and firm compliance and governance requirements.
• Deploy and scale models to production environments, ensuring robustness and reliability.
• Fine-tune models for optimal performance and efficiency, addressing any issues that arise.
• Work closely with data scientists, software engineers, and product teams to integrate machine learning solutions into existing systems and workflows.
• Continuously monitor model performance, making necessary adjustments to maintain and improve accuracy and efficiency.

Required Qualifications, Capabilities, and Skills:

• Proficiency in Python.
• Experience with one or more of the following: PyTorch, MLFlow, TensorFlow, or Scikit-learn.
• Strong understanding of software engineering principles and practices, including version control, testing, and code optimization.
• Skills in data preprocessing, feature engineering, and building data pipelines. Experience with Apache Spark, particularly PySpark.
• Experience with AWS Cloud Platform and Databricks for deploying and managing machine learning models.