AI/ML Engineer
Omni Inclusive
Job Title
Key Responsibilities:
• Develop, maintain, and enhance existing applications that utilize both Generative AI and traditional Machine Learning.
• Work extensively with Large Language Models (LLMs) to build and refine AI powered features.
• Collaborate with stakeholders to understand and translate business requirements into technical specifications for AI engineering projects.
• Conduct experiments, implement new technologies, and contribute to the rapid evolution of our AI capabilities.
• Lead the migration of existing projects, including those with agents and LLMs, to our Google Cloud Platform (GCP) environment.
• Engage in full-stack development, with a focus on Python for backend services and React for frontend interfaces.
• Perform data analysis using SQL to query and manipulate data from MS SQL Server, MySQL, and other relational databases.
Required Qualifications:
• Bachelor's degree in Computer Science, Engineering, or a related field.
• A minimum of 2-3 years of professional experience in an AI or Machine Learning engineering role. Experience with Python is a must.
• Demonstrated experience with concepts such as MCP, RAG, Semantic search, Generative AI, LLMs, and building agent-based systems. Ability to stay up to date with new and upcoming technologies around AI development (ex: Agentic RAG)
• Strong proficiency in Python for backend development and machine learning.
• Solid experience with React for frontend development.
• Expertise in SQL and experience working with relational databases such as MS SQL Server and MySQL.
• Hands-on experience with GCP AI/ML services, including BigQuery, Google SQL and other technologies and APIs within GCP.
• Ability to quickly grasp new requirements, experiment with new technologies, and adapt to a rapidly changing environment.
• Experience in taking over existing AI/ML applications from other teams.
• Estimate at a high level cost of usage in GCP for applications hosted/deployed
• Familiar with functional and non-functional testing of AI/ML applications and operationalizing it in production
Other Qualifications:
• Familiarity with Amazon Web Services (AWS), LLM models trending in the industry.
• A portfolio of projects demonstrating your expertise in AI and full-stack development.
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