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AI/ML Engineer

Prosum

Glendale, AZ

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JOB DETAILS
SALARY
$60–$75 Per Hour
SKILLS
Agile Programming Methodologies, Amazon Web Services (AWS), Artificial Intelligence (AI), Best Practices, Business Case, Cloud Computing, Code Reviews, Computer Programming, Computer Science, Continuous Deployment/Delivery, Continuous Improvement, Continuous Integration, Cross-Functional, Data Processing, Data Science, Documentation, Ecosystems, Emerging Technology, Identify Issues, Java, Machine Learning, Maintain Compliance, Metadata, Model Validation, Modeling Languages, NoSQL, Operational Support, Problem Solving Skills, Production Systems, Python Programming/Scripting Language, Reliability Engineering, SQL (Structured Query Language), Software Engineering, Structured Data, Technical Writing, Technical/Engineering Design, Test Automation, Test Requirements, Unstructured Data, Usability Engineering, Use Cases, User Interface/Experience (UI/UX)
LOCATION
Glendale, AZ
POSTED
30 days ago

AI/ML Engineer
Pay Range: $60/hour to $75/hour 

Job Summary
We are seeking a skilled and motivated AI/ML Engineer to join a growing Data & AI Platform Engineering team. In this role, you will contribute to the design, implementation, and support of AI and machine learning capabilities operating within an enterprise data and AI ecosystem.

The ideal candidate will collaborate with engineers, data scientists, and cross-functional stakeholders to deliver production-ready AI/ML solutions that are scalable, secure, and aligned with established engineering standards. This position requires strong software engineering fundamentals, experience working with unstructured data and metadata, and familiarity with semantic modeling techniques that enhance data discoverability and usability.

This role also offers the opportunity to work with emerging AI technologies, including Large Language Models (LLMs) and foundation model platforms, within a governed enterprise environment.

Key Responsibilities

AI/ML Solution Development
  • Design, develop, and support AI and machine learning components in partnership with senior engineers and architects.
  • Build secure, reliable, and maintainable AI/ML solutions using established engineering best practices.
  • Apply existing frameworks and standards to ensure consistency, scalability, and operational readiness.
  • Evaluate trade-offs involving performance, scalability, cost, and user experience when implementing solutions.

Unstructured Data & Semantic Technologies
  • Develop pipelines to ingest, process, and enrich unstructured and semi-structured data, including documents and text.
  • Work with metadata, embeddings, and semantic representations to improve search, retrieval, and downstream AI use cases.
  • Apply semantic modeling techniques to enhance data discoverability and usability across applications and end users.

Software Engineering Excellence
  • Write high-quality, production-grade code following modern development standards.
  • Participate in automated testing, code reviews, and CI/CD processes supporting AI/ML systems.
  • Translate technical designs into functional solutions and consistently deliver against commitments.

Collaboration & Problem Solving
  • Implement solutions for moderately complex technical challenges while considering business requirements and constraints.
  • Partner with data scientists, platform engineers, and business stakeholders to deliver effective AI/ML capabilities.
  • Contribute to technical documentation, design discussions, and agile development activities.

MLOps & Operational Support
  • Support MLOps/FMOps practices, including model deployment, versioning, monitoring, and troubleshooting.
  • Identify opportunities to improve reliability, observability, and maintainability of AI/ML systems.
  • Enhance existing pipelines, tools, and platform components through continuous improvement efforts.

Large Language Models & Foundation Models
  • Apply LLMs and prompt engineering techniques to address business use cases within established governance frameworks.
  • Contribute to solutions leveraging managed foundation model platforms.
  • Evaluate and assist in integrating emerging AI capabilities into enterprise platforms.

Governance & Compliance
  • Develop AI/ML solutions that align with organizational governance standards, including documentation, testing, and lineage requirements.
  • Collaborate with governance and compliance teams to ensure adherence to enterprise expectations.
  • Follow established practices related to model validation, versioning, and transparency.

Qualifications

Education
  • Bachelor's degree in Computer Science, Data Science, Engineering, or a related field required.
  • Advanced degree preferred.

Experience
  • 3+ years of experience in AI/ML engineering or applied machine learning.
  • Demonstrated experience delivering AI/ML solutions in production environments.
  • Hands-on experience working with unstructured data, embeddings, and semantic technologies.
  • Exposure to MLOps/FMOps practices and governed AI environments.
  • Experience with LLMs and prompt engineering is preferred.

Technical Skills
  • Strong programming skills in Python; experience with Java or similar languages is a plus.
  • Experience with AI/ML frameworks such as TensorFlow, PyTorch, and/or Scikit-learn.
  • Experience deploying AI/ML workloads within cloud environments, preferably AWS.
  • Familiarity with managed foundation model platforms (e.g., AWS Bedrock) is preferred.
  • Experience with data processing technologies such as Spark, SQL, and/or NoSQL databases.

About the Company

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