ML Systems Engineer Inference & Performance

The Ai Training Company; United States; Presencial; USD 120.000 - 180.000; Jornada completa

Descripción de la vacante

The Ai Training Company is seeking experienced Machine Learning Engineers, Researchers, AI Engineers, and ML Systems Engineers to contribute to a technically challenging AI training project in the United States. You will build and validate models, create reproducible training and inference workflows, and optimize performance across latency, throughput, and memory.

Ideal candidates have advanced degrees and strong Python proficiency, plus experience with multiple ML frameworks (e.g., PyTorch,

Formación

• Master’s degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Statistics, Engineering, Physics, or a closely related quantitative discipline
• Strong professional or research experience in machine learning
• Strong practical proficiency with Python
• Meaningful experience with at least two modern ML frameworks, libraries, or inference tools
• Strong understanding of machine learning model training, evaluation, numerical computation, or inference
• Ability to debug ML systems beyond basic high-level API usage
• Ability to understand tensor operations, model behavior, and implementation details
• Experience creating reproducible technical workflows
• Ability to evaluate whether an implementation is objectively correct
• Strong technical communication and documentation skills
• Ability to clearly explain implementation decisions, performance tradeoffs, and failure modes

Responsabilidades

• Develop and validate machine learning models and components
• Build reproducible training and inference workflows
• Implement model architectures, tensor operations, data pipelines, tokenization, batching, and generation systems
• Review and debug AI-generated machine learning code
• Diagnose numerical instability, incorrect tensor behavior, memory issues, and performance regressions
• Optimize inference and training for latency, throughput, memory consumption, and hardware utilization
• Compare multiple model implementations for correctness, efficiency, and reproducibility
• Build benchmarks and objective evaluation criteria
• Develop tests that verify model behavior and performance
• Debug distributed and system-level ML failures
• Document technical decisions, engineering tradeoffs, assumptions, and limitations
• Create reference implementations and technically rigorous solutions

Conocimientos

Python

Distributed training

Model architectures

Tensor operations

Data pipelines

Performance optimization

Debug ML systems

Multi-GPU training

NLP

GPU optimization

PyTorch

JAX

Educación

Master’s degree in Computer Science/ML/AI or related field

PhD in quantitative discipline

Herramientas

PyTorch

JAX

llama.cpp

TensorRT-LLM

vLLM

Descripción del empleo

The Ai Training Company is seeking experienced Machine Learning Engineers, Researchers, AI Engineers, and ML Systems Engineers to contribute to a technically challenging AI training project in the United States. You will build and validate models, create reproducible training and inference workflows, and optimize performance across latency, throughput, and memory.

Ideal candidates have advanced degrees and strong Python proficiency, plus experience with multiple ML frameworks (e.g., PyTorch,