Position: Senior Data Engineer
Location: Centennial, Colorado
Clearance: Must have a TS/SCI
Primary Responsibilities:
Data Pipeline Development: Build and maintain data pipelines that handle the ingestion, conversion, and processing of raw data into formats suitable for machine learning models.
Metadata and Tagging Management: Implement tagging and annotation tools to enhance data used for model training, ensuring efficient metadata storage and retrieval.
Database Management: Design and maintain databases for storing structured/unstructured data, including tags and metadata.
Preprocessing & Automation: Automate the preprocessing of data (e.g., cleaning, normalization, augmentation) to prepare it for neural network models.
MLops Integration: Work with machine learning engineers to implement end-to-end machine learning workflows, integrating data pipelines with model training, deployment, and monitoring processes.
Model Deployment and Monitoring: Set up and manage infrastructure for deploying machine learning models, including maintaining inference servers and continuous integration pipelines.
Model Versioning: Implement model version control and management systems to track experiments and ensure smooth transitions between model iterations.
Qualifications:
Experience with machine learning workflows, including data pipelines and model deployment.
Familiarity with working with unstructured and structured data, converting them for use in machine learning models.
Strong understanding of MLops practices, including model versioning, monitoring, and CI/CD for machine learning models.
Experience in scaling infrastructure to handle large datasets and multiple models in production.
Skills:
MLops Tools: Experience with MLops tools and platforms like Kubeflow, MLflow, or Seldon, including model tracking, deployment, and monitoring systems.
Data Engineering Tools: Airflow, Bash, Docker, Docker Compose, GDAL, Git, Linux, make, MongoDB.
NVIDIA Ecosystem: Expertise in NVIDIA installations (CUDA, cuDNN, Drivers, NVIDIA CONTAINER TOOLKIT).
Python: Expertise in Python (Dask, Faker, Jupyter, NumPy, pandas, pydantic, pymongo, pytest).
Data Conversion and Processing: Experience with data conversion libraries such as Rasterio and RAY.
Web & API Development: Experience with Traefik and hosting tools.
Database Management: Strong experience with managing metadata and tagging in databases like MongoDB, with scalable storage solutions.
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