ML Operations Engineer - Decision Science

JP Morgan

Location: Greater London

Job Type: Full time

Posted

The most difficult thing is the decision to act, the rest is merely tenacity.
- Amelia Earhart

ML Operations - Chase UK

Here at JPMorgan Chase & Co., we know that people want great value combined with an excellent experience, from a bank they can trust. So we launched a new digital bank called Chase – to revolutionise mobile banking by creating seamless digital journeys that our customers love. For us, that means keeping ourselves customer obsessed and always being open to trying new things. Above all, it's about working with people who are passionate about building the bank of the future.

Our team is at the heart of building this new venture, focused on developing offerings that put the customer at the centre. We have created a new organization and we are looking for solution-oriented, commercially minded, customer-focused engineers, used to working in an agile environment who want to be a part of building something new from the ground up within a diverse and inclusive team.

Culture is as important to us and we are looking for intellectually curious, new technology passionate individuals who would like to expand their skills whilst working on a new exciting venture for the firm. Your work will have a massive impact, both on us as a company, as well as our clients and our business partners around the world.

Summary:

This is a hands-on ML Operations role within a green-field initiative. The ideal candidate will be involved actively with architecting, building, deploying and maintaining cloud-native, web-scale data science products.

Required Experience:

  • Academic qualification in a computer science or STEM (science, technology, engineering or mathematics) related field or the foreign equivalent
  • Professional experience working in an agile, dynamic and customer facing environment
  • Recent hands-on professional experience (actively coding) working as an ML engineer, back-end software engineer or data engineer
  • Extensive knowledge of Python preferred (other OOP languages acceptable)
  • Understanding of distributed systems and cloud technologies (AWS, GCP, Azure, etc.)
  • Experience with containers and container-based deployment environment (Docker, Kubernetes, etc.)
  • Experience in automating deployment, releases and testing in continuous integration, continuous delivery pipelines
  • Understanding of (distributed and non-distributed) data structures, caching concepts, CAP theorem
  • Understanding of data streaming and messaging frameworks (Kafka, Spark Structured Streaming, Flink, etc.)
  • Understanding of relational databases and experience with SQL (any dialect)
  • Understanding of Spark framework and its deployment
  • Experience in all stages of software development lifecycle (requirements, design, architecture, development, testing, deployment, release and support)

Desirable Technical Qualifications & Experience

  • Experience with a scheduling system (Airflow, Azkaban, etc.)
  • Understanding of security frameworks / standards
  • Understanding of RESTful APIs and web technologies
  • Understanding of distributed tracing and monitoring (Zipkin, OpenTracing, Prometheus, ELK stack, Micrometer metrics, etc.)
  • A solid approach to writing unit level tests using mocking frameworks, as well as automating component, integration and end-to-end tests

Soft Skills:

  • Ability to work in a collaborative environment and coach other team members on coding practices, design principles, and implementation patterns that lead to high-quality maintainable solutions.
  • Ability to work in a dynamic, agile environment within a co-located team
  • Ability to focus on promptly addressing customer needs
  • Ability to work within a diverse and inclusive team
  • Technically curious, self-motivated, versatile, and solution-oriented
  • Excellent written and verbal communication skills in English
You’ve got this!