AI/ML Engineer
RESPONSIBILITIES
• Participate in developing Generative AI & Traditional AI Platform Capabilities on enterprise on-prem and cloud platforms.
• AI model delivery to on-prem infrastructure and cloud platforms (GCP-Vertex AI, Azure ML)
• Building automation capabilities to deploy ML Models and LLM Models on the enterprise on-prem platform and cloud platform.
• Build and Deploy capabilities for automating model scoring/Inferencing of ML models and LLMs.
• Build and Deploy capabilities for data pipeline deployment standardization and model consumption by multiple LOBs.
• Collaborate with product owners, DevOps team, data engineers, support teams to define and drive end to end model scoring pipelines.
• Participate in day-to-day standups for platform capability build.
• Provide SME guidance for data teams on software engineering principles, model deployments, platform capabilities.
• Drive AI use case delivery end to end collaborating with Data scientists, Data Engineers, LOB Technology using standardized platform processes and capabilities.
• Support Production Issues partnering with production support.
REQUIREMENTS
• 4+ years of Python development experience
• 4+ years of big data experience needed (BigQuery, Hadoop or equivalent)
• 3+ years of experience in Al, ML or MLOps area
• 2+ years of experience in developing APls
• 1+ year of experience in LLM, Generative Al (developing capabilities or dev/ops)
• 1+ year of Document Al, Agent Builder/GCP search/conversation/Dialogflow
• 1+ year of experience in Vector Database, Model Development
• Experience in developing and implementing algorithms to automate data cleaning, normalization, and enrichment processes
• Experience in Data discovery, Data collection and Processing, Data transformation, Machine learning models and Business insights generation
• Excellent Understanding software development life cycle (SDLC), version control systems (e.g., Git), and debugging techniques
• Experience as trusted advisor to clients, recommending innovative Al solutions to address their unique business challenges.
WORK ENVIRONMENT
• Hybrid role - 3 days in the office inWaterford, MI
RESPONSIBILITIES
• Participate in developing Generative AI & Traditional AI Platform Capabilities on enterprise on-prem and cloud platforms.
• AI model delivery to on-prem infrastructure and cloud platforms (GCP-Vertex AI, Azure ML)
• Building automation capabilities to deploy ML Models and LLM Models on the enterprise on-prem platform and cloud platform.
• Build and Deploy capabilities for automating model scoring/Inferencing of ML models and LLMs.
• Build and Deploy capabilities for data pipeline deployment standardization and model consumption by multiple LOBs.
• Collaborate with product owners, DevOps team, data engineers, support teams to define and drive end to end model scoring pipelines.
• Participate in day-to-day standups for platform capability build.
• Provide SME guidance for data teams on software engineering principles, model deployments, platform capabilities.
• Drive AI use case delivery end to end collaborating with Data scientists, Data Engineers, LOB Technology using standardized platform processes and capabilities.
• Support Production Issues partnering with production support.
REQUIREMENTS
• 4+ years of Python development experience
• 4+ years of big data experience needed (BigQuery, Hadoop or equivalent)
• 3+ years of experience in Al, ML or MLOps area
• 2+ years of experience in developing APls
• 1+ year of experience in LLM, Generative Al (developing capabilities or dev/ops)
• 1+ year of Document Al, Agent Builder/GCP search/conversation/Dialogflow
• 1+ year of experience in Vector Database, Model Development
• Experience in developing and implementing algorithms to automate data cleaning, normalization, and enrichment processes
• Experience in Data discovery, Data collection and Processing, Data transformation, Machine learning models and Business insights generation
• Excellent Understanding software development life cycle (SDLC), version control systems (e.g., Git), and debugging techniques
• Experience as trusted advisor to clients, recommending innovative Al solutions to address their unique business challenges.
WORK ENVIRONMENT
• Hybrid role - 3 days in the office inWaterford, MI
