What are the responsibilities and job description for the AI Solution Architect & Governance Lead position at Artmac?
Who We Are
Artmac Soft is a technology consulting and service-oriented IT company dedicated to providing innovative technology solutions and services to Customers.
Job Description
Job Title : AI Solution Architect & Governance Lead
Job Type : W2 / C2C
Experience : 7-20 Years
Location : Atlanta, Georgia / Austin, Texas
Responsibilities
Artmac Soft is a technology consulting and service-oriented IT company dedicated to providing innovative technology solutions and services to Customers.
Job Description
Job Title : AI Solution Architect & Governance Lead
Job Type : W2 / C2C
Experience : 7-20 Years
Location : Atlanta, Georgia / Austin, Texas
Responsibilities
- Research, design, and develop advanced anomaly detection algorithms (e.g., isolation forests, one-class SVM, autoencoders, time series forecasting)
- Train and evaluate machine learning models on large and complex datasets.
- Develop and deploy real-time anomaly detection systems using scalable and efficient technologies.
- Collaborate with cross-functional teams to understand business needs and translate them into technical requirements.
- Monitor model performance, identify areas for improvement, and continuously retrain and optimize models.
- Stay abreast of the latest advancements in anomaly detection and machine learning research.
- Contribute to the development of the best practices and guidelines for machine learning model development and deployment.
- Communicate technical concepts effectively to both technical and non-technical audiences.
- 8 years of experience in developing and deploying machine learning models in production environments.
- Strong understanding of anomaly detection techniques and algorithms.
- Proficiency in Python and experience with machine learning libraries (e.g., sci-kit-learn, TensorFlow, PyTorch).
- Experience with data preprocessing, feature engineering, and model evaluation.
- Experience with cloud platforms (e.g., AWS, GCP, Azure) is a plus.
- Excellent communication and collaboration skills.
- Strong analytical and problem-solving skills.
- Passion for machine learning and a strong desire to learn and grow.
- Experience with time series analysis and forecasting.
- Experience with deep learning models (e.g., recurrent neural networks, convolutional neural networks).
- Experience with MLOps practices (e.g., model monitoring, versioning, and deployment).
- Master's or Ph.D. in Computer Science, Statistics, Mathematics, or a related field.
