Senior ML Ops Engineer - Artificial Intelligence Group

  • Posted 22 days ago | Updated 22 days ago

Overview

On Site
Full Time

Skills

Decision trees
Large Language Models (LLMs)
Vector Databases
Customer facing
Research
Capital market
Bloomberg
Unstructured data
Analytics
Finance
Clarity
Build tools
Network
CPU
GPU
Artificial intelligence
Training
Machine Learning Operations (ML Ops)
Object-Oriented Programming
Python
Mathematics
Computer science
Data structure
Algorithms
Honesty
Problem solving
Management
Machine Learning (ML)
PyTorch
Kubernetes
Workflow
Cloud computing
Amazon Web Services
Google Cloud
Google Cloud Platform
Microsoft Azure
Collaboration

Job Details

Bloomberg's Engineering AI department has 300+ AI practitioners building highly sought after products and features that often require novel innovations. We are investing in AI to build better search, discovery, and workflow solutions using technologies such as transformers, gradient boosted decision trees, large language models, and dense vector databases. We are expanding our group and seeking highly skilled individuals who will be responsible for contributing to the team (or teams) of Machine Learning (ML) and Software Engineers that are bringing innovative solutions to AI-driven customer-facing products.

At Bloomberg, we believe in fostering a transparent and efficient financial marketplace. Our business is built on technology that makes news, research, financial data, and analytics on over 35 million financial instruments searchable, discoverable, and actionable across the global capital markets.

Bloomberg has been building Artificial Intelligence applications that offer solutions to these problems with high accuracy and low latency since 2009. We build AI systems to help process and organize the ever-increasing volume of structured and unstructured information needed to make informed decisions. Our use of AI uncovers signals, helps us produce analytics about financial instruments in all asset classes, and delivers clarity when our clients need it most.

We are looking for Senior MLOps Engineers with strong expertise and passion for building and maintaining AI systems to join our team.
As a Senior MLOps Engineer you will design and build tools to improve the efficiency of our Model Development Life Cycle (MDLC), automate ML processes, enhance the performance of our systems and more.


Join the AI Group as a Senior MLOps Engineer and you will have the opportunity to:


  • Architect, build, and diagnose production AI applications and systems
  • Collaborate with colleagues on production systems and write, test, and maintain production quality code
  • Define and provide strong SLAs around latency, throughput and resource (memory / disk / network / CPU / GPU) usage
  • Work closely with AI Platform teams to operationalize continuous model training, inference, and monitoring workflows


We are looking for a Senior MLOps engineer with:

  • 4+ years of experience working with an object-oriented programming language (Python, Go, etc.)
  • A Degree in Computer Science, Engineering, Mathematics, similar field of study or equivalent work experience
  • An understanding of Computer Science fundamentals such as data structures and algorithms
  • An honest approach to problem-solving, and ability to collaborate with peers, stakeholders and management
  • Industry experience with machine learning teams
  • Working knowledge of common ML frameworks such as PyTorch, ONNX, DeepSpeed etc.
  • Prior experience with cloud-native technologies like Kubernetes, Argo Workflows, Buildpacks, etc.
  • Experience with cloud providers such as AWS, Google Cloud Platform or Azure
  • A track record of collaboration with colleagues to achieve repeatable high quality outcomes
We give back to the technology community and you can read more about our outreach at:
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.