Senior Software Engineer - AI Inference
Track this application
Get Started FreeMatch score against your CV
Get Started FreeTailor your resume to this job
Get Started FreeAbout interviewing at Bloomberg
Three to five stages over four to seven weeks: a recruiter screen where a generic 'Why Bloomberg?' is an early exit, one or two HackerRank CodePair phone screens on LeetCode-medium DSA, then a ~4-hour virtual onsite of two harder coding rounds (graphs, trees, DP — you explain correctness without running code), a practical finance-flavored system design round for mid/senior roles, a hiring-manager deep-dive on past technical decisions, and a short HR close. Teams run their own processes (some add a PR-style code-review round; some skip design), and you can interview with multiple teams.
Read the full Bloomberg interview process →Description
Our team: Join the team that is building the core infrastructure for AI at Bloomberg. The Bloomberg AI Inference Platform provides production-grade managed infrastructure for hosting, deploying, and serving all machine learning models, both predictive and cutting-edge generative models. We abstract away infrastructure complexity, empowering engineering teams to focus on creating intelligent applications with guaranteed scalability, performance, and governance. Our platform is built on the open-source KServe project, and the CNCS AI Inference team is a primary contributor to its development.
We'll trust you to:
You'll need to have:
We'd love to see:
Representative projects:
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.
We'll trust you to:
- Design and build scalable infrastructure for both online and offline inference workloads.
- Lead integration of high-performance inference runtimes and serving frameworks, including TensorRT, vLLM, ONNX, and Triton.
- Drive architecture and technical decisions across Bloomberg’s inference platform, balancing latency, throughput, reliability, and cost.
- Partner across engineering teams to improve model deployment, observability, and production performance.
- Mentor junior engineers on system design, debugging, and performance optimization.
You'll need to have:
- 5+ years of professional software engineering experience.
- Experience designing, building, and operating production distributed systems.
- Strong systems intuition and a track record of debugging and optimizing performance-critical services.
- Ability to own problems end-to-end and quickly ramp up in unfamiliar technical areas.
- 4+ years of demonstrated experience working with an object-oriented programming language.
- A degree in Computer Science, Electrical Engineering, or equivalent practical experience.
We'd love to see:
- Experience deploying and operating machine learning systems at scale.
- Experience with inference optimization techniques such as batching, caching, request scheduling, or memory-aware serving.
- Familiarity with PyTorch and GPU software stacks such as CUDA and NCCL.
- Exposure to high-performance interconnects and distributed computing technologies such as NVLink, InfiniBand, or MPI.
- Experience with Kubernetes and cloud-native infrastructure.
- Experience with load balancing, request routing, or traffic management systems.
Representative projects:
- Autoscaling a heterogeneous compute fleet to match supply and demand aross diverse inference workloads.
- Building production-grade deployment pipelines to safely roll out new models to millions of users.
- Developing new inference capabilities such as structured sampling, prompt caching, and advanced serving optimizations.
- Analyzing observability data from real production workloads to improve latency, throughput, and resource efficiency.
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.
More engineering roles at Bloomberg
Senior Data Management Professional - Data Engineering (Shared Infrastructure)New
Bloomberg·London
Senior Software Engineer - Cloud StabilityNew
Bloomberg·New York·$160K - $240K
Senior Data Management Professional - Data Automation Engineer - People DataNew
Bloomberg·Princeton·$110K - $190K
Senior Data Management Professional - Data Engineer - BNEF Data, TokyoNew
Bloomberg·Japan
Senior Software Engineer - Artificial Intelligence
Bloomberg·New York·$160K - $240K