Senior ML Engineer - Production Systems & LLMs

Tech Ladies, Inc.; Raleigh (NC); Presencial; USD 120.000 - 180.000; Jornada completa

Descripción de la vacante

Tech Ladies, Inc. is seeking an ML Engineer to own design, training, and production deployment of ML systems powering core product features, including tabular ML, NLP, and emerging LLM-based workflows.

In a small, senior team, you will tackle issues of model performance, latency, and reliability, shipping systems that run in production rather than notebooks. Expect collaboration with data engineering and an emphasis on rigorous evaluation and monitoring.

Formación

• 3–7 years of experience with multiple production model deployments.
• Expert-level Python and hands-on depth in PyTorch, TensorFlow, or scikit-learn.
• Production experience with cloud ML platforms and MLOps tooling (MLflow, model registries, CI/CD for ML).
• Strong ML fundamentals: feature engineering, evaluation design, and handling drift.
• Experience with Docker/Kubernetes and serving systems such as TorchServe, Triton, or FastAPI.

Responsabilidades

• Design, train, and evaluate ML models for production workloads.
• Build and maintain feature pipelines in Python and SQL, ensuring training-online consistency.
• Deploy and version models using Docker, Kubernetes, and cloud ML platforms with CI/CD for releases.
• Instrument models for monitoring: drift, latency, and business metrics with automated retraining triggers.
• Collaborate with data engineering to build reliable data pipelines using Spark, Airflow, and modern tooling.
• Introduce LLM-based capabilities with RAG, embeddings, and fine-tuning with rigorous evaluation.
• Contribute to code reviews, design docs, and ML engineering standards.

Conocimientos

Python

Deep learning frameworks

Cloud ML platforms

MLOps tooling

ML fundamentals

Containerized deployment

CS degree relevance

Educación

MS/BS in CS or related

Herramientas

Docker

Kubernetes

TorchServe/Triton/FastAPI

MLflow

Descripción del empleo

Tech Ladies, Inc. is seeking an ML Engineer to own design, training, and production deployment of ML systems powering core product features, including tabular ML, NLP, and emerging LLM-based workflows.

In a small, senior team, you will tackle issues of model performance, latency, and reliability, shipping systems that run in production rather than notebooks. Expect collaboration with data engineering and an emphasis on rigorous evaluation and monitoring.