Machine Learning Engineer

at Nvidia

USD 152,000-241,500 per year

MIDDLE

✅ On-site

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

AI @ 6 Automated Testing CI/CD Data Analysis @ 5 Data Pipelines Design Patterns @ 6 GPU @ 6 Git @ 5 Kubernetes @ 3 LLM LangChain @ 6 Machine Learning Pandas @ 5 Performance Monitoring @ 3 PyTest @ 2 PyTorch @ 3 Python @ 5 SGLang @ 6 Slurm @ 3 System Architecture @ 6 TensorFlow @ 3 scikit-learn @ 3 vLLM @ 6

Details

NVIDIA is seeking a Machine Learning Engineer to drive the development, evaluation, deployment, and end-to-end lifecycle management of AI-powered systems. The role combines advanced AI application development with robust software engineering and continuous automation, including the use of AI agents, automated testing frameworks, and secure GitLab CI/CD pipelines. The position also involves deploying and scaling models across distributed infrastructure, managing GPU orchestration, prompt-tuning models, and building advanced AI workflows with Kubernetes, Ray, or Slurm.

Responsibilities

Architect, deploy, and scale open-source models using distributed orchestration frameworks such as Kubernetes, Ray, and Slurm to support highly available and fault-tolerant AI workloads.
Design and build machine learning systems and data pipelines.
Design experiments, prompt-tune, evaluate, and deploy production-grade models and AI agents.
Implement flexible mechanisms to benchmark performance and quickly swap models for evolving use cases.
Run comprehensive model benchmarks and perform detailed error and gap analysis on model outputs.
Build analytics dashboards to communicate system performance findings to technical and non-technical stakeholders.
Own features independently from ideation through production, including architectural decisions, coordination across accessible and restricted code repositories, and community interactions.

Requirements

Master’s or PhD in Computer Science, Electrical Engineering, or a related field, or equivalent experience.
At least 3 years of professional experience writing production-grade asynchronous Python.
Strong focus on decoupled, clean system architecture and design patterns.
Deep experience with LangChain, Hugging Face libraries, vLLM, and SGLang.
Experience with TensorFlow, PyTorch, and Scikit-learn.
Proficiency in data analysis using Python, pandas, NumPy, or similar tools.
Ability to extract insights from model evaluation results and communicate findings clearly.
Hands-on experience with production-grade model deployment, performance monitoring, analysis, and scaling using Kubernetes, Ray, or Slurm.
Experience managing multi-node cluster configurations.
Strong understanding of GPU memory management and infrastructure-level tuning for high-throughput, low-latency AI inference workflows.
Advanced knowledge of GitLab pipelines, including automated test jobs and vulnerability scanner integration into merge request workflows.
Expert familiarity with Python testing frameworks such as PyTest, mocking libraries, and automated test generation frameworks for AI workloads.
High proficiency in advanced Git workflows, including rebase strategies, cryptographic commit signing, and complex public/private repository mirroring.

Preferred Qualifications

Experience with alignment or fine-tuning of large language models, vision-language models, or any-to-text models.
Passion for AI and demonstrated commitment to advancing the field through innovative research.
Prior scientific research and publication experience.

Compensation and Benefits

Base salary range: USD 152,000–241,500 per year.
Eligible for equity and benefits.
Applications will be accepted at least until September 12, 2026.
NVIDIA is an equal opportunity employer committed to an inclusive work environment.