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Added 11 hours ago
Senior Software Engineer (AI-Native)
Telegent, Inc.
Pleasant Grove, UT
Distributed systems and data. Deep, hands-on experience across transactional, wide-column, streaming, analytical, ledger, cache and object stores, and the judgment to use each one well.
Added 17 hours ago
Senior Storage Engineer
Runware
Remote, United States
As Senior Storage Engineer, you will own the storage architecture of Runware's AI supercomputer: how model weights, caches and customer data move from object storage on two continents to…
Added 17 hours ago
Principal Engineer, Model Performance
Runware
Remote, United States
…of pods and tens of thousands of GPUs, all operated as one distributed fabric that reroutes traffic the moment a pod goes offline…
Added 3 days ago
Senior/Staff System Research Engineer - LLM Inference Optimization
Snowflake Inc.
Bellevue, WA
Our work spans the full inference stack-from distributed serving and runtime systems to GPU kernels and model-system co-design. We explore techniques such as adaptive parallelism,…
Added 3 days ago
Performance & Debug Software Engineer – AI Inference
Positron AI
Remote, United States
This engineer will improve end-to-end large language model (LLM) inference performance on Positron's custom AI accelerators, including our FPGA-based Atlas systems and our Titan systems…
Added 3 days ago
Sr Lead Software Engineer – Java & Trading Platform
JPMC page
Jersey City, NJ
As a Senior Lead Software Engineer at JPMorganChase within Asset & Wealth Management, you are an integral part of an agile team that works to enhance, build, and deliver trusted…
Added 3 days ago
Senior Pre-Sales Systems Engineer, SLED (San Francisco / East Bay)
Everpure
Remote, United States
…flash technology space, is seeking a talented and motivated Senior Pre-Sales Systems Engineer to join our dynamic…
Added 4 days ago
Lead eCommerce Engineer
CITY HOME
Tamarac, FL
…that drive conversion and SEO to the AWS, search, and caching systems that power them. You will also coach and mentor Senior Software Engineers and Software Engineers. Your contributions…
Added 4 days ago
Senior Software Engineer – Backend
Marriott
Bethesda, MD
As a Senior Software Engineer – Backend at Marriott, you will design, develop, and support scalable, secure, and high-performance backend services that power Marriott’s global digital…
Added 5 days ago
Senior Software Engineer (Backend), Retail & Marcom Engineering
Apple
Sunnyvale, CA
Experience with message-driven and event-driven architectures, including proficiency in messaging systems (e.g. Kafka, RabbitMQ, ActiveMQ, etc.), event sourcing, CQRS patterns, and…
Added 5 days ago
Senior Machine Learning Infrastructure Engineer, Matchmaking
Roblox
San Mateo, CA
As a Senior Machine Learning Infrastructure Engineer, you’ll build scalable, reliable, and high-performance infrastructure that powers ML systems across our organization. You’ll operate at…
Added 5 days ago
Senior Developer Experience Engineer-AI Infrastructure Operations
Nscale
NY
This is a senior engineering role for someone who sets the bar for how Nscale ships software and then pulls the rest of the team up to it. You'll own the hardest problems on the delivery…
Added 5 days ago
Senior Software Engineer – Backend
Marriott
Remote, United States
As a Senior Software Engineer – Backend at Marriott, you will design, develop, and support scalable, secure, and high-performance backend services that power Marriott’s global digital…
Added 7 days ago
Senior Performance Engineer - LLM Inference Frameworks
NVIDIA Corporation
North District, IL · Haifa District, IL
Design and experiment with memory management strategies for improved memory bandwidth optimization and cache efficiency
Added 7 days ago
AE
Sr Software Engineer II
American Express
New York, NY
- $123,000 to $215,250 USD / year
This is a hands-on senior engineering role at the intersection of Salesforce, Google Cloud Platform (GCP), data engineering, APIs, distributed systems, and data security. The engineer will…
Added 9 days ago
O
Senior/Staff Software Engineer - Tech Lead
OpenMined
Remote, United States
- $125,000 to $258,000 USD / year
We're looking for a Senior / Staff Software Engineer to join OpenMined, a nonprofit building open-source infrastructure for federated AI.
Added 9 days ago
Principal Software Engineer
Mirantis
Remote, United States
As Principal Software Engineer, you are the senior technical voice for Enterprise AI. You own its architecture together with the teams that share the platform, and set the technical bar for…
Added 10 days ago
Principal Engineer - AI/ ML - Home Broadband Solutions
Verizon Data Services LLC
Irving, TX
…AI-generated number trustworthy. The role will be responsible for the distributed query engines, streaming data, broadband device data models and production LLM engineering, along with the…
Added 10 days ago
R
Senior Principal AI Engineer
Rapid7
Remote, United States
- $255,900 to $346,200 USD / year
As a Senior Principal AI Engineer, you will set the technical direction for how Rapid7 builds, tunes and serves LLMs and agentic systems across its security products. You understand LLMs…
Added 10 days ago
AI Engineer
Zoom Communications, Inc.
Seattle, WA
You will build and optimize the inference systems that serve Zoom's AI models in production. Working alongside senior inference engineers, research and platform teams, you will profile…
Added 10 days ago
Senior Software Architect, AI Systems and Networking
NVIDIA USA
Remote, United States
Understanding of ML systems concepts - transformer architectures, KV cache mechanics, model parallelism, or distributed training and inference patterns.
Added 10 days ago
Senior Pre-Sales Systems Engineer, SLED (Albany)
Everpure
Remote, United States
…flash technology space, is seeking a talented and motivated Senior Pre-Sales Systems Engineer to join our dynamic…
Added 10 days ago
Sr. Backend Software Engineer (Infrastructure ML Ops)
Philo
San Francisco, CA · Brooklyn, NY · Cambridge, MA
SENIOR BACKEND SOFTWARE ENGINEER (INFRASTRUCTURE MLOPS)
Added 10 days ago
G
Senior Backend Engineer - Onsite
Genesis10
Richfield, MN
- $70 to $80 USD / hour
…catalog management, product ranking, and fulfillment options. The engineer will work on highly scalable, distributed backend systems and will have opportunities to drive technical design…
Added 10 days ago
RH
Senior Machine Learning Engineer (vLLM)
Red Hat, LLC
United States
- $186,160 to $287,410 USD / year
…optimization; LLM inference optimization, including quantization, KV cache or batching; distributed computing including inter and intra GPU communication protocols; and leading technical…

Netflix

Staff/ Principal Software Engineer (L6/L7): AI Platform Model Serving

United States

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Job details

Apply by: May 1, 2027
Experience: With relevant experience in the AI/ ML Infrastructure and distributed systems for 12+ years.
Posting language: English
Posted: Nov 2, 2026

Original job description

At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next.

Netflix is on the journey to rebuild the AI/ML model serving platform and infrastructure that turns trained models into served predictions across real-time, async, and agentic workloads, at a scale few companies operate at. Supporting many production clusters, from classical to foundation models, spanning latencies from milliseconds rankers to LLM calls, and powering everything members see from homepage ranking to search, messaging, and internal AI productivity tools.

We are re-building a new model serving platform from the ground up, designed from first principles to meet industry standards. It unifies our in-house inference infrastructure, third-party model hosting, and external LLM providers under a single serving, routing, and experimentation layer. Teams get one consistent way to deploy, route, and A/B test any model, regardless of where it runs.

Re-engineering how GPU capacity is provisioned and used. During off-peak periods, the same fleet that serves latency-critical production traffic is repurposed to run open-weight models for internal coding and developer productivity use cases.

This role sits at the center of Netflix’s GenAI and Foundation Model serving strategy, with real R&D scope on frontier AI infrastructure. You will tackle the efficiency problems that most directly drive cost per inference and capacity: disaggregated serving, intelligent routing across models and providers, speculative decoding, prompt caching, and multi-GPU inference. These are the levers that turn GPU spend into measurable business value.

You will lead the technology behind some of Netflix’s largest bets, embedding AI capabilities into member-facing products at global scale. You will also build durable, resumable execution for long-running agentic workloads. Online and asynchronous/ Near-Real-Time inference is projected to grow fast in 2028, so getting this foundation right now is what keeps costs sustainable and reliability high as demand scales.

Looking for deep expertise in distributed systems and high-performance RPC, GPU/CPU inference optimization, control planes, and experimentation infrastructure, plus fluency with modern LLM serving stacks and a track record of architecting systems that hold together under both extreme scale and rapid technology change.

Qualifications and Expectations

To succeed in this role, you will need:

Have a BS/MS/PhD in Computer Science, Applied Math, Engineering, or a related field. With relevant experience in the AI/ ML Infrastructure and distributed systems for 12+ years.
Influence without authority to guide architectural decisions and alignment across multi-teams through trust, data, and demonstrated expertise.
Shape long-term technical roadmaps (typically looking 2 to 3 years ahead) and ensure scalability, maintainability, and business alignment.
Cross-Functional Partnership: Work closely with product managers, operations, and executive stakeholders to balance technical trade-offs with business priorities.
Clear Communication skill to translate dense technical concepts for non-technical stakeholders and produce clear documentation, architecture decision records (ADRs), and proposals.
Have experience with high-traffic distributed services and infrastructure for AI/ ML model inference, with a focus on high availability, security, and performance.
Have experience building scalable model-serving solutions for Foundation Models that powers generative and predictive AI applications with practical skills in reducing latency and costs.
Familiar with deploying AI/ ML models using platform and solutions such as NVIDIA Triton Inference Server, vLLM, or SGLang, and scaling them via Kubernetes.
Have experience working with public cloud infrastructure providers such as AWS, Azure, or GCP.

Preferred Qualifications:

Have open-source contributions to projects in the AI/ML, distributed systems, or infrastructure space.
Hands-on experience with building AI models, and have explored optimization techniques for AI models, such as quantization, model compression, or model pruning.
Proficient in leveraging AI coding tools in software development.
Have experience working with model gateway and intelligent routing for choosing the right AI models based on context of the requests.
Exposure to deploying multi-adapters model serving, disaggregated prefill/decode, or large-scale KV cache management.
Working with evaluation and benchmarking tools for LLMs and AI Agents.
Knowledge of GPU topology, NVIDIA CUDA programming, and machine learning compilers.

Key technologies & ecosystem

Deep Learning frameworks: Pytorch, TensorFlow, JAX, Hugging Face Transformers
Inference Engines and Runtimes: vLLM, SGLang, TensorRT-LLM, TGI (Text Generation Inference), DeepSpeed-Inference, NVIDIA Dynamo
Hardware and Low-Level: CUDA, NCCL, and profiling tools like NVIDIA Nsight.

To learn more about our AI Platform, you can review the relevant talks/blog posts on the Netflix AI Platform Research website.

Generally, our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $890,000.00 - $1,690,000.00. This compensation range will vary based on location.

Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer paid leave of absence programs. Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off. See more details about our Benefits here.

Netflix is a unique culture and environment. Learn more here.

Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner.

We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.

Job is open for no less than 7 days and will be removed when the position is filled.

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More about this job

Skills

Computer science
ML
Communication skills
Documentation
Kubernetes
AWS
Microsoft Azure
Google Cloud
Software development
Machine learning
Deep learning
PyTorch
TensorFlow
Hugging Face
Research
Mental health

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