Applied AI ML [Multiple Positions Available]

DESCRIPTION:

Duties: Build and train production-grade Machine Learning on large-scale datasets to solve various business use cases for Global Banking. Use large scale data processing frameworks for feature engineering and be proficient across various data both structured and unstructured. Use Deep Learning models and Generative AI techniques for solving various business use cases including multi-source data fusion information retrieval question-answering forecasting and anomaly detection. Build ML models across Public and Private clouds including container-based Kubernetes environments. Develop end-to-end ML pipelines necessary to transform existing applications and business processes into robust Artificial Intelligence systems. Build both batch and real-time model prediction pipelines with existing application and front-end integrations. Collaborate to develop large-scale data modeling experiments evaluating against strong baselines and extracting key statistical insights and cause and effect relationships.

QUALIFICATIONS:

Minimum education and experience required: Bachelors degree in Computer Engineering Computer Science Information Systems Data Science Artificial Intelligence Machine Learning or related field of study plus 3 years (36 months) of experience in the job offered or as Applied AI ML Associate Software Engineer Software Engineering Program Analyst or related occupation. The employer will alternatively accept a Masters degree in Computer Engineering Computer Science Information Systems Data Science Artificial Intelligence Machine Learning or related field of study plus 1 year (12 months) of experience in the job offered or as Applied AI ML Associate Software Engineer Software Engineering Program Analyst or related occupation.

Skills Required: This position requires experience with the following: Managing and transforming structured and unstructured data using Pythonic implementations of normalization aggregation data cleaning enrichment entity extraction or sentiment analysis; Validating data quality and completeness; Implementing anomaly detection methods and building robust reusable features for AI/ML teams; Conducting data analysis modeling and engineering tasks required in end-to-end AI/ML solution design and implementation using Python SQL and PySpark; Exploring visualizing and analyzing data to create and validate proof-of-concept AI/ML engineering solutions; Applying machine learning and statistical techniques including regression classification clustering time series analysis dimensionality reduction and mathematical optimization to address business challenges; Developing evaluating and training AI/ML models taking ownership of the full implementation lifecycle including hyperparameter tuning model selection and performance evaluation; Writing optimized code in SQL Spark and Python leveraging cloud technologies and cloud analytics platforms; Designing and deploying scalable distributed statistical and AI/ML models in production environments using containerization and CI/CD pipelines; Building and maintaining end-to-end data pipelines for model deployment and operationalization with embedded performance monitoring; Communicating documenting and presenting machine learning results and insights to non- technical audiences; Delivering AI/ML solutions with cross-functional teams such as Data Engineering Model Operations or Design; Conducting research and development work to evaluate emerging AI/ML methods algorithms and best practices; Translating academic research into use- case specific implementations and practical solutions; Demonstrating proficiency in MLOps practices model monitoring automated retraining data privacy and compliance in AI/ML workflows version control systems RESTful API development for model serving distributed computing frameworks and experiment tracking tools.

Job Location: 3223 Hanover St Palo Alto CA 94304.

Full-Time. Salary: $177500 - $260000 per year.