AI ML Engineer

Overview

On Site
Depends on Experience
Contract - Independent
Contract - W2
Contract - 12 Month(s)
Able to Provide Sponsorship

Skills

Kubernetes
Generative Artificial Intelligence (AI)
Google Cloud Platform
Continuous Monitoring
PyTorch
Good Clinical Practice
Big Data

Job Details

Role : AI ML Engineer

Location : Charlotte NC (2 roles) & 1 role (NY NJ) - Day 1 onsite

Model Development: Design, develop, and deploy machine learning models using the Tachyon platform.
Data Engineering: Prepare and preprocess data for model training.
Pipeline Development: Build robust data and ML pipelines for efficient model workflows.
Model Training & Tuning: Train and fine-tune machine learning models, optimizing for latency and throughput.
AI Workflow Documentation: Develop playbooks and templates for AI workflow automation.
 Deployment & Integration: Collaborate with engineers for efficient deployment and integration of models into applications.
Monitoring & Improvement: Implement continuous monitoring of models to track performance, data drift, and model reliability
5+ years of experience in machine learning, especially in NLP, generative AI, and model deployment.
Expertise in TensorFlow, PyTorch, or scikit-learn.
Experience with cloud platforms (AWS, Google Cloud Platform, Azure) and Kubernetes for AI workload scaling.
Familiarity with MLOps, SQL, and big data frameworks (Hadoop, Spark).

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