AIML Engineer
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Job Location:
San Antonio, TX - USA
Monthly Salary:
Not Disclosed
Posted on:
Yesterday
Vacancies:
1 Vacancy
Job Summary
Job Description
AI/ML Solutions Engineer
Job Summary
Seeking a talented and driven AI/ML Solutions Engineer to join a team and play a pivotal role in designing and deploying intelligent systems that enhance operational efficiency and automate workflows. This is a hands-on high-impact position that involves collaboration across finance operations and leadership teams. The ideal candidate will have expertise in building machine learning pipelines and developing scalable AI-driven solutions with a particular focus on Generative AI and LLM-based applications.
Compensation Package
- Competitive salary commensurate with experience
- Comprehensive health dental and vision insurance
- Generous paid time off and holidays
- Professional development opportunities
- Flexible work arrangements
Responsibilities
AI / Generative AI Development
- Design and deploy AI/ML solutions using Google Cloud tools such as Vertex AI and APIs.
- Identify and implement high-value use cases including document processing summarization Q&A systems and workflow automation.
- Develop and optimize prompt engineering RAG pipelines and model tuning strategies.
- Ensure AI solutions meet standards for accuracy explainability and compliance.
- Apply safeguards such as data redaction access controls and secure prompt handling.
ML Engineering & Infrastructure
- Build and maintain end-to-end ML pipelines including data ingestion deployment and monitoring.
- Leverage tools such as BigQuery Dataflow and orchestration frameworks.
- Establish and implement MLOps best practices including CI/CD model versioning and monitoring.
- Design and maintain security-focused architecture including encryption IAM/least-privilege access secure APIs and logging/auditability.
Collaboration & Stakeholder Engagement
- Partner with business teams to identify automation opportunities and translate business requirements into scalable AI/ML solutions.
- Communicate technical concepts effectively to non-technical stakeholders.
- Drive adoption of AI capabilities across the organization.
Qualifications/Requirements
Required Qualifications
- Bachelors degree in a related technical field.
- 35 years of experience in AI/ML data science or engineering roles.
- Hands-on experience with Google Cloud tools such as Vertex AI and BigQuery.
- Proficiency in working with LLMs prompt engineering and RAG frameworks.
- Strong programming skills in Python and familiarity with ML frameworks like TensorFlow PyTorch or scikit-learn.
- Knowledge of secure development practices and cloud security fundamentals.
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Required Experience:
IC
Key Skills
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