Senior Deep Learning Software Engineer, Inference
Nvidia
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This role on the market
175 open inference roles across 47 companies are on ApplySarthi right now, most of them in Delhi NCR (2), Bengaluru (2).
- Staff Machine Learning Engineer, LLM Inference Optimization Nebius
- (Staff / Senior Staff) AI Infra Engineer, Inference InfrastructureTogether AI
- Senior Software Engineer (AI Inference & Runtime Platform)Jobgether
- Systems Software Engineer (AI inference stack, CUDA)Micron
- Senior IA Inference Engineer (x/f/m)Doctolib
What inference roles keep asking for: LLMs (67%), Python (61%), Machine learning (45%), PyTorch (41%), System design (28%), C++ (27%), Kubernetes (27%), Observability (27%) — counted across their open postings here.
C++ jobs · Deep learning jobs · Generative AI jobs · LLMs jobs
Nvidia has 3,054 open roles listed here.
- Senior Solutions Architect – Large Scale AI Training
- Senior Solutions Architect – Large Scale Neural Networks Inference
- Senior Infrastructure Automation Engineer, Compute Platform - EDA Infrastructure
- Senior Cloud Infrastructure and DevOps Solutions Architect
- Senior Software Development Engineer, Neural Graph Infrastructure
Counted across 14 company job boards, updated as roles open and close.
Preparing for this interview
Interviews for inference roles keep coming back to LLMs, Python, Machine learning, PyTorch. Practise those questions before you sit with Nvidia.
Questions you are likely to be asked
- Why do you want to join Nvidia?
- What is your experience with Deep learning? Tell me one thing you learned the hard way.
- When would you not use machine learning for a problem?
- Walk me through a model you built, from the data to how it was used.
- How did you know your model was actually good, and not just good on your test set?
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Practise the Senior Deep Learning Software Engineer, Inference at Nvidia interview free →NVIDIA seeks a Senior Software Engineer specializing in Deep Learning Inference for our growing team. As a key contributor, you will help design, build, and optimize the GPU-accelerated software that powers today’s most sophisticated AI applications. Our team is responsible for developing and maintaining high-performance open-source frameworks, which are at the forefront of efficient large-scale model serving and inference. You will play a central role in improving these platforms, facilitating smooth deployment and serving of groundbreaking language models. You’ll work closely with the deep learning community to implement the latest algorithms for public release in inference frameworks. Your work will focus on identifying and driving performance improvements for state-of-the-art LLM and Generative AI models across NVIDIA accelerators, from datacenter GPUs to edge SoCs. You'll bring to bear open-source tools and plugins—including CUTLASS, OAI Triton, NCCL, and CUDA kernels—to implement and optimize model serving pipelines. What you'll be doing: Performance optimization, analysis, and tuning of DL models in various domains like LLM, Multimodal and Generative AI. Scale performance of DL models across different architectures and types of NVIDIA accelerators. Contribute features and code to NVIDIA’s inference libraries, vLLM and SGLang, FlashInfer and LLM software solutions. Work with cross-collaborative teams across frameworks, NVIDIA libraries and inference optimization innovative solutions. What we need to see: Masters or PhD or equivalent experience in relevant field (Computer Engineering, Computer Science, EECS, AI). 5+ years of relevant software development experience. You'll need excellent C/C++ programming and software design skills. SW Agile skills are helpful and Python experience is a plus. Prior experience with training, deploying or optimizing the inference of DL models in production is a plus. Prior background with performance modeling, profiling, debug, and code optimization or architectural knowledge of CPU and GPU is a plus. GPU programming experience (CUDA, OAI TRITON or CUTLASS) is a plus. Ways to Stand out from The Crowd Contribute to deep learning software projects, such as PyTorch, vLLM, and SGLang to drive advancements in the field. Experience with Multi GPU Communications (NCCL, NVSHMEM) With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to outstanding growth, our special engineering teams are growing fast. If you're a creative and autonomous engineer with a genuine passion for technology, we want to hear from you! #LI-Hybrid Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until October 16, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
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Listed on workday · posted 2026-10-12. ApplySarthi collects openings and links to application pages; the role is advertised by Nvidia, not by us.