Overview
Read on to find out what you will need to succeed in this position, including skills, qualifications, and experience.
Collaborate with corporate teams to design and implement AI solutions improving decision-making and automating workflows.
Develop machine learning models tailored to structured and unstructured data for diverse business applications.
Optimize AI processes, including prompt engineering and retrieval strategies, ensuring high performance and relevance.
Engage stakeholders to identify impactful AI use cases and deliver measurable business outcomes.
Experiment with emerging AI techniques to enhance productivity and reduce manual efforts.
Ensure compliance with responsible AI practices, including data privacy and governance.
Document technical processes and solutions to support scalability and reuse across teams.
Provide technical guidance and mentorship on AI best practices within the organization.
Hybrid schedule: 3 days onsite and 2 days remote per week.
Work Authorization:
W2 only
Key Responsibilities & Duties
Design and deploy AI-driven solutions enhancing business processes and user productivity.
Develop machine learning models for practical applications, ensuring high accuracy and relevance.
Optimize AI workflows, including embeddings and retrieval strategies, for improved outcomes.
Collaborate with stakeholders to translate business needs into effective AI solutions.
Experiment with new AI methodologies to innovate and streamline operations.
Maintain responsible AI practices, including transparency and governance.
Document AI models and processes for scalability and team collaboration.
Provide expertise on AI technologies and practices to support organizational goals.
Job Requirements
Bachelor of Science degree in a relevant field is required.
Minimum of 3 years of experience in AI or machine learning development, with 5 years preferred.
Proficiency in Python programming and experience with Azure OpenAI or similar platforms.
Expertise in generative AI, prompt engineering, and retrieval-augmented generation.
Strong understanding of embeddings, vector search, and semantic retrieval techniques.
Experience with structured and unstructured data, including text-heavy datasets.
Knowledge of MLOps practices, model versioning, and monitoring in production environments. xsgimln
Microsoft or AI-related certifications are beneficial.