Job Title: Google Machine Learning Work Location: Charlotte, NC 28214 (Onsite)
Contract duration: 6
Target Start Date: 10 Jul 2023
Must Have Skills:
-Vertex AI
-GCP
-ML
Experience:
5+ years of relevant experience in Google cloud
5+ Years of experience in working with Data Science, ML, ML Ops, Python technologies in any of the cloud environment
Significant experience architecting cutting-edge MLOps systems in enterprise environments using GCP Vertex AI
5+ years of experience building, scaling, and optimizing enterprise-grade Machine Learning systems, using frameworks such as scikit-learn, XGBoost, TensorFlow and Spark
3+ years of experience designing and building data-intensive, production-ready solutions using distributed computing frameworks such as Spark
3+ years of experience developing and deploying Machine Learning solutions on Google Cloud.
Mastery of data wrangling in rational databases using SQL
Knowledge of object-oriented programming design best practices
Professional services experience
GCP Professional Machine Learning Engineer certification preferred
Nice to have skills:
-GCP AutoML
-Python
Detailed Job Description:
Strong experience in working with Goggle Cloud Platform (GCP) cloud-based architectures and technologies to deliver optimized ML models at scale using Vertex AI
Strong experience in ML, Data Science, Deep Learning, NLP
Hands on experience using Vertex AI in GCP extensively for Developing and Deploying ML Models
experience in working with Auto ML in GCP
Experience in Deploying ML models using GCP managed services. Strong hands on experience in ML Ops.
Deliver production ML software models and components that solve real-world business problems, while working in collaboration with product and application teams
Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment
Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art, next generation big data and machine learning applications
Construct optimized data pipelines to feed ML models
Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code
Advocate for software and machine learning engineering best practices
Function as a technical or project lead and while mentoring junior engineering talent
