Machine Learning Engineer

Client: Leading Financial Services Organization

Location: Hybrid

Our client is seeking a Machine Learning Engineer to join a multidisciplinary Agile team responsible for developing, deploying, and supporting mission-critical data systems, microservices, web applications, and AI/ML solutions. This role supports the full Application Lifecycle Management (ALM) process, working alongside software engineers, data scientists, and business stakeholders to design, build, deploy, and maintain enterprise AI solutions with a strong focus on AWS cloud technologies.

Key Highlights:

• Design, develop, and deploy machine learning models utilizing AWS services including SageMaker, Lambda, EC2, S3, and Redshift.
• Support automated model training and deployment workflows using AWS Step Functions and Lambda.
• Monitor, evaluate, and optimize machine learning model performance.
• Participate in the complete software development lifecycle including analysis, design, development, testing, deployment, and production support.
• Collaborate with cross-functional Agile teams to deliver scalable AI and software solutions.
• Manage, prepare, and process datasets using AWS data services.
• Contribute to CI/CD pipelines, DevSecOps initiatives, automated testing, and software configuration management.
• Participate in code reviews, design sessions, and technical best practice discussions.
• Create and maintain technical documentation for machine learning models, workflows, and system architecture.
• Provide Level II production support and contribute to continuous operational improvements.
• Ensure compliance with data privacy, security, and organizational governance standards.

Qualifications:

• Bachelor's degree in Computer Science, Data Science, Information Technology, or a related discipline preferred.
• 1–3 years of professional experience developing AI/ML solutions within enterprise applications.
• Experience building cloud-native solutions using AWS technologies including SageMaker, Lambda, EC2, S3, Glue, Athena, Redshift, DynamoDB, Aurora, EventBridge, Kinesis, SNS, SQS, and related services.
• Strong programming experience with C# and proficiency in Python, SQL, JavaScript, or PowerShell.
• Experience with machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Understanding of object-oriented analysis/design (OOA/OOD), distributed systems, microservices architecture, event-driven design, and API development.
• Experience with Docker, Git/GitHub, and CI/CD platforms including Jenkins, Bamboo, TeamCity, or AWS CodePipeline.
• Familiarity with automated testing frameworks such as SpecFlow or Cucumber.
• Experience working with SQL and NoSQL databases, messaging platforms (Kafka, MQ, JMS), JSON, and modern JavaScript frameworks such as Angular or React.
• Excellent analytical, communication, documentation, and problem-solving skills.
• Experience within insurance, financial services, or other highly regulated industries is highly preferred.

Preferred Qualifications:

• AWS Certified Machine Learning – Specialty and/or AWS Certified Solutions Architect (Associate).
• Experience with Generative AI, Natural Language Processing (NLP), Computer Vision, or Reinforcement Learning.
• Familiarity with Azure cloud-native technologies.
• Experience with Agile, Kanban, Lean, or XP methodologies.

EEO Policy:

Allied Resources complies with all Equal Employment Opportunity (EEO) affirmative action laws and regulations. Allied Resources does not discriminate on the basis of age, race, religion, color, sex, national origin, marital status, genetic information, sexual orientation, gender identity and expression, disability, veteran status, or any other status protected by applicable law.