Gen AI Solution Architect
Location-Washington DC (Onsite)
(1.) Key Responsibilities
1. Architect end-to-end AI/ML solutions using Python, TensorFlow, PyTorch, and scikit-learn, ensuring robust model development and deployment frameworks.
2. Design scalable data pipelines and real-time processing systems utilizing Apache Spark, Kafka, and PostgreSQL to support machine learning workflows.
3. Guide the team in implementing advanced ML models, including deep learning, NLP, and time series forecasting, using tools such as XGBoost, LightGBM, and Spark MLlib.
4. Oversee integration of data engineering platforms like Apache Airflow, DataBricks, and RabbitMQ to optimize data ingestion, transformation, and orchestration for AI/ML projects.
5. Ensure technical excellence by advocating best practices in model validation, performance optimization, and reproducibility across Python, R, and SQL-based environments.
6. Collaborate with stakeholders to gather requirements, translate business needs into technical specifications, and deliver tailored AI/ML solutions that meet quality and compliance standards.
7. Mentor and coach team members in advanced AI/ML concepts, fostering continuous learning and adoption of emerging technologies within the skill cluster.
8. Architect and implement RESTful API integrations to enable seamless communication between AI/ML components and external systems, ensuring scalable, secure, and efficient data exchange across diverse enterprise environments.
Skill Requirements
1. Expert Proficiency In Ai/Ml Model Development, Including Classical Machine Learning, Deep Learning, Nlp, And Time Series Forecasting.
2. Excellent Knowledge Of Python, R, Sql, And Bash For Data Analysis, Model
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