Machine Learning Engineer (Contract, Edison, NJ (Local Only & Day1 Onsite) at Edison, New Jersey, USA |
Email: [email protected] |
Need Local only Position: Machine Learning Engineer Location: Edison, NJ (Day1 Onsite) Duration: Contract Job Description: 10+ years of engineering experience (Masters degree in Computer Science, Engineering, or a related technical field is a plus) Programming Skills Expert knowledge in Python and SQL Comfortable with libraries like pandas, numpy, scikit-learn, tensorflow, pytorch, keras, huggingface, langchain Strong track record of implementing ML models, deploying these, and maintaining them in production environments Strong understanding of fundamental computer science and statistics/ML concepts Proficient with data structures, algorithms, automated testing, object-oriented programming Proficient with linear/logistic regression, SVM, random forest, boosting, neural networks, dimensionality reduction, reinforcement learning, etc. Familiar with performance complexity and implications of computer architecture on software performance Model Deployment and Production environment Experience deploying genAI applications is a plus Experience using, designing and developing microservices and associated APIs Experience working in accordance with DevSecOps principles, and familiarity with industry deployment best practices using CI/CD tools and infrastructure as code (Docker, Kubernetes, Containers, Git, Terraform) Experience with cloud platforms (e.g. AWS, Azure) and associated ML products, e.g. Amazon SageMaker Lalit Kumar Sr. Technical Recruiter Envision Technology Solutions E: [email protected] Phone: 315-832-9494 Ext 125 Direct: 609-757-4467 10130 Mallard Creek Rd, Charlotte NC, 28262 Lalit Kumar Sr. Technical Recruiter Envision Technology Solutions E: [email protected] Phone: 315-832-9494 Ext 125 Direct: 609-757-4467 -- Keywords: continuous integration continuous deployment machine learning information technology New Jersey North Carolina Machine Learning Engineer (Contract, Edison, NJ (Local Only & Day1 Onsite) [email protected] |
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Fri Jun 14 19:01:00 UTC 2024 |