Technology Lead: AI/ML on AWS & Cloud Data

Veriipro; North Palm Beach (FL); On-site; USD 130,000 - 190,000; Full time

Job summary

Veriipro seeks an experienced Technology Lead – Data on Cloud / AWS to design, build, and productionize ML solutions. You will lead data science and engineering efforts, shaping scalable data pipelines and model deployment across cloud environments.

Responsibilities include developing ML/DL models, collaborating with stakeholders, ensuring data quality and security, and driving innovation with AI technologies in a fast-paced setting.

Qualifications

• Hands-on experience designing, developing, deploying ML solutions on cloud platforms.
• Proficient in Python and ML/DL frameworks.
• Experience with data pipelines for model training and deployment.
• Ability to work with cloud providers (AWS, Azure, Google Cloud).

Responsibilities

• Develop, train, test, and optimize ML and DL models.
• Analyze large datasets to identify patterns, trends, and insights.
• Design and implement AI solutions for predictive analytics, automation, NLP, and computer vision.
• Build and maintain data pipelines supporting model training and deployment.
• Deploy AI/ML models into production environments and monitor model performance.
• Collaborate with data scientists, software developers, and business stakeholders.
• Perform model evaluation, tuning, and continuous improvement.
• Ensure data quality, security, and compliance with organizational standards.
• Troubleshoot production issues and perform root‑cause analysis.
• Research and implement emerging AI/ML technologies and best practices.
• Prepare technical documentation and present technical findings to stakeholders.

Skills

AWS core services

Python programming

Machine learning

Deep learning

Data pipelines

Analytical thinking

AI/ML deployment

Tools

TensorFlow

PyTorch

Scikit-learn

Keras

Job description

Veriipro seeks an experienced Technology Lead – Data on Cloud / AWS to design, build, and productionize ML solutions. You will lead data science and engineering efforts, shaping scalable data pipelines and model deployment across cloud environments.

Responsibilities include developing ML/DL models, collaborating with stakeholders, ensuring data quality and security, and driving innovation with AI technologies in a fast-paced setting.