TL;DR

Junior AI / Machine Learning Engineer (AWS): Developing, deploying, and supporting enterprise-grade data platforms, microservices, web applications, and AI/ML solutions with an accent on AWS-based machine learning development, model deployment, and cloud-native engineering. Focus on assisting with model design, development, training, deployment, and monitoring, and participating in the full Application Lifecycle Management (ALM) process.

Location: West Chester, PA (Hybrid)

Company

%hirify_global% provides staffing for a multidisciplinary Agile team focused on AI/ML solutions.

What you will do

Assist in the design, development, training, deployment, and monitoring of machine learning models using AWS services (SageMaker, Lambda, EC2, S3, Redshift).
Support automated ML workflows for training, testing, and deployment using AWS Step Functions, Lambda, and CI/CD pipelines.
Monitor model performance and assist with tuning, retraining, and optimization.
Develop and maintain microservices and APIs supporting ML and data workflows.
Manage, preprocess, and analyze datasets using AWS data services.
Participate in code reviews, design reviews, and Agile ceremonies while supporting DevSecOps practices.

Requirements

Bachelor’s degree in Computer Science, Data Science, Information Technology, or related field (preferred).
1–3+ years of professional experience in AI/ML, data engineering, or software development.
Hands-on experience with AWS cloud services, especially SageMaker, Lambda, EC2, S3.
Proficiency in Python and experience with machine learning libraries such as TensorFlow, PyTorch, scikit-learn.
Familiarity with microservices architecture and distributed systems concepts.
Experience with version control (Git) and CI/CD tools (Jenkins, AWS CodePipeline).
Understanding of basic DevOps and DevSecOps practices.

Nice to have

Experience in financial services, insurance, or other regulated industries.
Familiarity with additional AWS services such as Glue, Athena, DynamoDB, Kinesis, or Redshift Spectrum.
Exposure to containerization tools (Docker).
Experience with SQL and relational or NoSQL databases.
Knowledge of NLP, computer vision, reinforcement learning, or generative AI concepts.

Culture & Benefits

Hybrid work environment.
Opportunity to work on mission-critical enterprise AI initiatives.
Receive mentorship from senior engineers.
Work in an Agile, fast-paced environment.

Junior AI / Machine Learning Engineer (AI)