Production ML Engineer: LLMs, Pipelines & Deployment

Tech Ladies®; Raleigh (NC); On-site; USD 120,000 - 170,000; Full time

Job summary

Tech Ladies® in Raleigh is seeking a senior ML Engineer to own design, training, and production deployment of machine learning systems powering core features. You’ll tackle performance, latency, and reliability in production-grade workloads beyond notebooks.

You will work with a senior team to deploy models, build robust data pipelines, and champion LLM-based capabilities. This role demands strong Python skills, cloud ML experience, and a passion for scalable ML systems.

Qualifications

• 3–7 years of experience in ML engineering, applied ML, or related role
• Expert-level Python and hands-on depth in PyTorch, TensorFlow, or scikit-learn
• Production experience with cloud ML platforms and MLOps tooling
• Strong ML fundamentals: feature engineering, evaluation design, regularization, drift
• Experience with containerized deployment (Docker, Kubernetes) and serving systems such as TorchServe/Triton/FastAPI
• MS or BS in Computer Science, Statistics, Engineering, or equivalent practical experience

Responsibilities

• Design, train, and evaluate ML models for production workloads
• Build and maintain feature pipelines in Python and SQL
• Deploy and version models using Docker, Kubernetes, and cloud ML platforms
• Instrument models for monitoring: track drift, latency, and business metrics
• Collaborate with data engineering to build reliable data pipelines using Spark, Airflow
• Introduce and champion LLM-based capabilities with RAG, embeddings, fine-tuning
• Contribute to code reviews, design docs, and ML engineering standards

Skills

Python

ML fundamentals

Communication

Problem solving

Education

MS or BS in CS/Statistics/Engineering

Tools

Docker

Kubernetes

SageMaker

Vertex AI

Azure ML

MLflow

Airflow

TorchServe

Triton

FastAPI

Spark

Job description

Tech Ladies® in Raleigh is seeking a senior ML Engineer to own design, training, and production deployment of machine learning systems powering core features. You’ll tackle performance, latency, and reliability in production-grade workloads beyond notebooks.

You will work with a senior team to deploy models, build robust data pipelines, and champion LLM-based capabilities. This role demands strong Python skills, cloud ML experience, and a passion for scalable ML systems.