AWS Artificial Intelligence (AI) Engineer
Job title: AWS Artificial Intelligence (AI) Engineer in New York City, NY at The Data Sherpas
Company: The Data Sherpas
Job description: Who We Are:We are a dynamic team focused on delivering cutting-edge AI and machine learning solutions on Amazon Web Services (AWS). Our AWS Artificial Intelligence Engineer will be at the forefront of designing, developing, and implementing AI/ML models to solve complex business challenges, collaborating closely with data scientists, software engineers, and business stakeholders.What We Are Looking For:We are seeking a highly skilled and innovative AWS Artificial Intelligence (AI) Engineer who will design, develop, and deploy AI and ML solutions using AWS's advanced services. The ideal candidate will have deep expertise in AI/ML frameworks, cloud-based data processing, and automation, with a strong focus on scalability and high-performance AI solutions.Responsibilities:AI/ML Solution Design and Development:
- Design and implement AI/ML models using AWS services such as SageMaker, Comprehend, Rekognition, Lex, and Translate.
- Develop and deploy scalable machine learning models using TensorFlow, PyTorch, and Scikit-learn.
- Build and optimize data pipelines using AWS Glue, Kinesis, S3, and Redshift to support AI/ML workflows.
- Ensure AI solutions are efficient, scalable, and reliable in a production environment.
- Design and implement machine learning training pipelines on AWS.
- Optimize model performance through hyperparameter tuning and algorithm selection using SageMaker Autopilot and Hyperparameter Tuning.
- Monitor model accuracy and retrain models as needed to maintain performance.
- Work with structured and unstructured data to create datasets for training and evaluation.
- Automate data ingestion and preprocessing using AWS Glue, Kinesis, and Athena.
- Ensure data quality and integrity for AI/ML workflows.
- Implement CI/CD pipelines for AI/ML models using CodePipeline, CodeBuild, and SageMaker Pipelines.
- Deploy machine learning models using SageMaker Endpoints and monitor performance in real time.
- Ensure model governance, versioning, and auditing processes are followed.
- Collaborate with business stakeholders to identify AI opportunities and translate them into technical solutions.
- Evaluate new AI and ML technologies on AWS to improve existing solutions.
- Provide technical guidance and thought leadership on AI best practices.
- Ensure AI solutions comply with company security policies and industry regulations.
- Implement access controls, data encryption, and secure APIs using IAM and KMS.
- Monitor and audit cloud environments for security vulnerabilities and risks.
- Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field; Master’s or Ph.D. is a plus.
- 3+ years of experience designing and implementing AI/ML solutions on AWS.
- AWS Certified Machine Learning – Specialty certification is required.
- Strong proficiency with AWS services such as SageMaker, Comprehend, Rekognition, Lex, Glue, Kinesis, and Athena.
- Hands-on experience with machine learning frameworks like TensorFlow, Keras, PyTorch, and Scikit-learn.
- Proficiency in programming languages such as Python, Java, or Scala.
- Experience with MLOps and CI/CD tools, including CodePipeline, CodeBuild, and SageMaker Pipelines.
- Strong understanding of AI/ML algorithms, data structures, and model optimization techniques.
- Experience with containerization (Docker, Kubernetes) and orchestration using ECS and EKS.
- Strong analytical, problem-solving, and communication skills.
- Experience with natural language processing (NLP) and computer vision solutions using AWS tools.
- Experience with automated feature engineering and model interpretability.
- Familiarity with data lake and data warehouse architectures on AWS.
- Strong understanding of cloud security and access controls using IAM and KMS.
- Competitive salary and performance-based incentives.
- Comprehensive health, dental, and vision coverage.
- 401(k) with company matching.
- Professional development and training opportunities (including AWS certification).
- Flexible work environment and remote work options.