AI/ML Engineer

We are seeking an experienced AI/ML Engineer to join our team in Jersey City, NJ. In this role, you will design and implement scalable infrastructure and tools to support machine learning initiatives across the enterprise. This position involves close collaboration with Data Scientists to create ML platforms and operationalize AI/ML models at scale, enabling impactful business outcomes in financial services. Key Responsibilities Design, develop, and maintain frameworks for deploying and managing ML models in production environments Collaborate with Data Scientists to develop and scale predictive models and machine learning solutions Extend and optimize existing ML platforms to enable efficient training and inference Build cloud-native applications using AWS services such as SageMaker, Bedrock, S3, CloudFormation, Lambda, and Step Functions Implement CI/CD pipelines using Jenkins and manage source code with Git Develop containerized applications using Docker and manage infrastructure using CloudFormation, Terraform, or OpenTofu Design distributed systems for large-scale data processing and ML workflows Partner with engineering and business teams to support the adoption of AI/ML solutions Create tools to monitor model performance, detect data drift, and automate diagnostics Explore and implement emerging technologies to evolve the ML ecosystem Required Qualifications

Bachelor’s or Master’s degree in Computer Science, Engineering, or related field 5+ years of experience in developing Python-based cloud applications and/or machine learning solutions Strong proficiency in Python and its ML libraries (numpy, pandas, sklearn, tensorflow) Solid experience with Linux scripting and familiarity with Java and Groovy (basic knowledge is a plus) Proven expertise with AWS services for AI/ML, including SageMaker and Bedrock Familiarity with Azure Cognitive Services (especially OpenAI) and Google Vertex AI is a plus Experience with CI/CD tools like Jenkins and containerization using Docker Expertise in infrastructure as code (IaC) using AWS CloudFormation and tools like Terraform Strong understanding of scalable, distributed system development Experience working with Agile methodologies (Kanban, SCRUM) Experience with data wrangling, including structured, semi-structured, and unstructured data Preferred Qualifications

Experience with feature engineering and developing reusable feature stores Familiarity with monitoring tools for model performance and uncertainty Knowledge of applied data science methods and machine learning algorithms

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