AI Specialist(MLops, Sage Maker - Only W2)

Summary: We are seeking a skilled Machine Learning Engineer/AI Specialist to join our dynamic team. The ideal candidate will have extensive AWS SageMaker, strong Python programming skills, a solid background in data science, and a deep understanding of MLOps practices. Top Skills: Python, MLOps, AWS SageMaker Only W2, Not on C2C or 1099 Key Responsibilities: • Design, develop, and deploy machine learning models using AWS SageMaker platform. • Build and maintain ML pipelines for training, validation, and deployment of models. • Implement MLOps best practices including CI/CD for machine learning workflows. • Collaborate with data scientists to productionize research models. • Monitor model performance and implement automated retraining processes. • Optimize model inference performance and cost efficiency. • Develop and maintain model versioning and experiment tracking systems. • Ensure data quality and implement data validation frameworks. • Create comprehensive documentation and technical specifications. • Participate in code reviews and maintain high coding standards. • Debug Terraform and Concourse errors. • Proactively update pipelines based on changes made by other organizations. • Migrate repository to GitHub and update pipelines accordingly. Required Qualifications: • Bachelor's degree in Computer Science, Data Science, Engineering, or related field; or 8 years of equivalent work experience. • 3+ years of experience in machine learning engineering or related roles. • Proficiency in Python programming with experience in ML libraries (pandas, numpy, etc.). • Familiarity with Infrastructure as Code (Terraform, CloudFormation). • Hands-on experience with AWS SageMaker for model training, tuning, and deployment. • Strong background in data science methodologies and statistical analysis. • Deep understanding of MLOps practices and tools (Docker, Kubernetes, CI/CD pipelines). • Experience with version control systems (Git Hub Actions) and collaborative development. • Knowledge of cloud platforms, preferably AWS (S3, EC2, Lambda, etc.). Preferred Qualifications: • Master's degree in a relevant field. • AWS certifications (Machine Learning Specialty, Solutions Architect, etc.). • Knowledge of containerization and orchestration technologies. • Experience with monitoring and observability tools (CloudWatch, Prometheus, etc.). • Experience with big data technologies (EMR, Spark, Hadoop, etc.). • Understanding of software engineering best practices and design patterns. • Good working experience in ETL (SSIS or Sqoop/Spark). • Experience with EMR • Expert SQL knowledge (All types of Joins, CTE’s, Indexes, Stored Procedures, SQL performance). • Knowledge in building basic machine learning models (Classification & Regression). • Knowledge in Docker/MLOps and its orchestrations. Key Skills & Competencies: • Strong analytical and problem-solving abilities. • Excellent communication and collaboration skills. • Ability to work in fast-paced, agile environments. • Detail-oriented with a focus on code quality and documentation. • Continuous learning mindset and adaptability to new technologies. • Experience working cross-functionally with data scientists, engineers, and product teams.