| Data Engineer with ML - Onsite - Locals to GA only at Atlanta, Georgia, USA |
| Email: [email protected] |
|
From: MANOJ Kumar Akkapelly, Msys Inc [email protected] Reply to: [email protected] Title: Data Engineer with ML - Onsite - Locals to GA only Location: Atlanta, GA, USA Length: Long term Restriction: W2 or C2C Send resumes to : [email protected] Description: **** Webcam interview *** Long term project *** *** Onsite *** *** Locals to GA only *** Need minimum experience: 7+ Years Responsibilities: Data Pipeline Development: Design, build, and maintain scalable data pipelines to support machine learning workflows. Data Integration: Integrate data from various sources, ensuring data quality and consistency. Model Deployment: Deploy machine learning models into production environments, ensuring they are scalable and reliable. Collaboration: Work closely with data scientists, ML engineers, and stakeholders to understand data requirements and deliver solutions. Performance Optimization: Optimize data processing workflows and machine learning model performance. Monitoring & Maintenance: Monitor data pipelines and ML models to ensure they function correctly and efficiently. Skills & Qualifications: Bachelors/Masters degree in Computer Science, Data Engineering, Machine Learning, or a related field. 7+ years of experience in data engineering, ML model deployment, and data pipeline development. Proficiency in programming languages such as Python, Java, and SQL. Experience with data engineering tools like Apache Spark, Hadoop, and Kafka. Familiarity with ML frameworks such as TensorFlow, PyTorch, or scikit learn. Hands on experience with cloud platforms like AWS, Google Cloud, or Azure. Strong database management skills with SQL and NoSQL databases. Ability to create data visualizations for communicating insights effectively. Nice To Have: Experience with MLOps and automated ML model lifecycle management. Knowledge of big data technologies for real time data processing. Hands on experience with containerization (Docker, Kubernetes) for ML model deployment. Experience in feature engineering and data preprocessing for ML models. Certifications in data engineering or ML (e.g., Google Professional Data Engineer, AWS Certified Machine Learning). Key Technical Tools & Technologies: Programming Languages: Python, Java, SQL. Data Engineering Tools: Apache Spark, Hadoop, Kafka. Machine Learning Frameworks: TensorFlow, PyTorch, scikit learn. Cloud Platforms: AWS, Google Cloud, Azure. Databases: SQL (PostgreSQL, MySQL), NoSQL (MongoDB, Cassandra). Deployment & Infrastructure: Docker, Kubernetes. Version Control & CI/CD: Git, GitHub Actions, Jenkins. Visualization Tools: Tableau, Power BI, Matplotlib, Seaborn. Keywords: continuous integration continuous deployment machine learning business intelligence wtwo Georgia Data Engineer with ML - Onsite - Locals to GA only [email protected] |
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| 01:37 AM 06-Mar-25 |