Machine Learning Engineer
Sterling, VA

Job Description

AI/Machine Learning engineer will develop and deploy full lifecycle AI/ML solutions at scale. Working with Data Scientists and Quantitative Analysts, you will own end to end ML engineering processes from data collection, cleaning, preprocessing, monitor model training and production deployment. Develop rapid prototypes and experiments in conjunction with Product Owners and Data Scientists. Serve as a liaison between analytics & technology teams to support Retail Business & Product function with innovative AI Solutions

Duties and Responsibilities:

Understand business use cases and work with Data Science and Quantitative Analysts to develop and deploy models

Codify common analytics/data science tasks into Python & R packages and/or Docker containers

Continuously improve ML task automation pipeline to enable rapid data product delivery

Curate and document ML engineering framework with examples/tutorials.

Serve as ML framework ambassador, teaching team members framework fundamentals and driving adoption

Implement CI/CD deployment standards and policies

Document and refactor code base as needed

Managing available resources such as hardware, data, and personnel so that deadlines are met

Communicate to owners, leadership in a clear, concise, and compelling manner

Identify opportunities and recommend creative solutions to business problems through analytics and understanding of the business processes and systems

Operate with a high degree of autonomy in a direct support relationship to primary customers and meet all requirements with minimal management oversight

Qualifications:

Bachelor's Degree in Computer Science, Software Engineering, Computer Engineering, Electrical Engineering, Electronics Engineering, or related field.

2 years' experience in a similar role with a hands-on track record of implementing AI/ML solutions using Python, Javascript, R, git

Knowledge of full or micro stack Python web development frameworks (Flask, Django, Bottle, Tornado)

Linux, Cloud experience to provision instances for development, deployment

Familiarity with containerizing processes with Docker

Ability to abstract and containerize ML prototypes into reusable building blocks

Familiarity managing & orchestrating container deployment (ECS, docker-swarm and/or Kubernetes)

Ability to write and execute moderate to complex SQL queries and manipulate disparate data sources

Understanding of Natural Language Processing, Computer Vision, or deep learning libraries and platforms desired (TensorFlow, Keras)

AWS experience preferred