Overview
On Site
Depends on Experience
Accepts corp to corp applications
Contract - W2
Contract - 12 Month(s)
Skills
Python
PyTorch
AWS
Azure
Job Details
** only 12 + yrs exp and local to Dallas, TX **
** Visa-independent candidate must work on a direct W2**
Role: Sr Machine Learning Engineer
Location: Hybrid onsite in Plano, TX
Long term
C2C is okay
Must have Skills:
- 12+ years of software engineering, machine learning, data science, or total equivalent experience
- Strong experience in Machine Learning, Computer Vision, and/or Signal Processing
- Experience working with the deployment and monitoring of ML models in a production cloud-based containerized environment
- Ability to write clean, concise, tested, maintainable code in Python
- Solid production experience with Deep Learning using TensorFlow and/or PyTorch
- Experience with designing, implementing, and maintaining machine learning pipelines in a production environment
- Experience in Agile practices and promoting Agile development techniques such as TDD, BDD and CI/CD
- Experience deploying ML models in a container environment
- Experience with public cloud, including AWS, Azure, or Google Cloud Platform
Responsibilities:
- Use statistical and machine learning techniques to create scalable solutions for vehicle telemetry data and video analysis, and perform R&D to drive the discovery of new generation mobility products
- Establish scalable, efficient, automated processes for large-scale data analysis, model development, model validation, and model implementation
- Drive adoption of best practices across organizations
- Deliver production-ready code
- Work with Product Owners to define the KPIs for machine learning projects
- Stay abreast of developments in research methodology and changing technologies in the marketplace, and proactively identify applications of these latest developments to improve existing methods
- Prepare and present findings to both technical and non-technical audiences
- Develop and foster collaborative relationships with product, business, and engineering teams to effectively serve our customers' needs
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