Who we are
Artmac Soft is a technology consulting and service-oriented IT company dedicated to providing innovative technology solutions and services to customers.
Job Description :
Job Title : Senior Python Backend Developer
Job Type : W2 / C2C
Experience : 8 15 years
Location : San Jose, California (Onsite)
Responsibilities :
- 8+ years of experience in MLOps, Machine Learning Engineering, or a specialized Inference Optimization role.
- A portfolio or project experience demonstrating successful deployment of high-performance, containerized ML models to production scale.
- Model-Specific Optimization : Analyze and understand the underlying logic and dependencies of various AI / ML models (primarily using PyTorch and TensorFlow) to identify bottlenecks in the inference pipeline.
- High-Performance Serving Implementation : Design, implement, and manage high-performance inference serving solutions utilizing specialized inference servers (e.g., vLLM) to achieve low latency and high throughput.
- GPU Utilization Optimization : Optimize model serving configurations specifically for GPU hardware to maximize resource efficiency and performance metrics in a production environment.
- Containerization for Deployment : Create minimal, secure, and production-ready Docker images for streamlined deployment of optimized models and inference servers across various environments.
- Collaboration : Work closely with core engineering and data science teams to ensure a smooth transition from model development to high-scale production deployment.
Required Skillsets :
AI / ML Domain Expertise
Deep understanding of the AI / ML domain, with the core effort centered around model performance and serving, rather than general infrastructure.ML Frameworks
Expertise in PyTorch and TensorFlow : Proven ability to work with and troubleshoot model-specific dependencies, logic, and graph structures within these major frameworks.Inference Optimization
Production Inference Experience : Expertise in designing and implementing high-throughput, low-latency model serving solutions.Specialized Inference Servers : Mandatory experience with high-performance inference servers, specifically including vLLM , or similar dedicated LLM serving frameworks.GPU Optimization : Demonstrated ability to optimize model serving parameters and infrastructure to maximize performance on NVIDIA or equivalent GPU hardware.Deployment and Infrastructure
Containerization (Docker) : Proficiency in creating minimal, secure, and efficient Docker images for model and server deployment.Infrastructure Knowledge (Helpful, but Secondary) : General knowledge of cloud platforms (AWS, GCP, Azure) and Kubernetes / orchestration is beneficial but the primary focus remains on model serving and optimization.Qualification :
Bachelor's degree or equivalent combination of education and experience.