Senior MLOps Engineer - Artificial Intelligence

AI in this role

pytorch

ml-ops

Bloomberg’s Engineering AI department has 400+ 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, GCP 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: http://www.techatbloomberg.com/ai

Salary Range = 160,000 - 240,000 USD Annual + Benefits + Bonus
The referenced salary range is based on the Company's good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education/training and skill level.

We offer one of the most comprehensive and generous benefits plans available and offer a range of total rewards that may include merit increases, incentive compensation (exempt roles only), paid holidays, paid time off, medical, dental, vision, short and long term disability benefits, 401(k) +match, life insurance, and various wellness programs, among others. The Company does not provide benefits directly to contingent workers/contractors and interns.
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How we rate this

Senior MLOps Engineer - Artificial Intelligence at Bloomberg rates 91 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

ML OpsPyTorch

Questions you could be asked

How do you monitor a model once it's live, and how do you know it needs retraining?
Walk me through how you've used PyTorch in your day-to-day work.
How would you decide a model or AI system is ready to ship?
Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

List these exact terms on your resume: ML Ops and PyTorch. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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