AI/Machine Learning Engineer
3 weeks ago
Locations:
Only considering profiles that are local to Ohio/Kentucky/Indiana at this time.
MUST HAVES:
8+ years of experience with Python engineering with expertise with large language modules
5+ machine learning and engineering
Machine learning builds generative AI models, understand how to condense or expand that data
Experience working with Azure cloud
Dealing with massive amounts of data – how much
6+ months with one of the following:
Prompt Engineering or, RAG (Retrieval Augmented Generation) or FineTuning
Plusses:
DevSec Ops
Azure DevOps
DAY 2 DAY:
A large Agriculture organization is seeking a Generative AI Engineer that will sit onsite in the Greater Cincinnati, Ohio area. We’re looking for a Generative AI Engineer to join our Artificial Intelligence team and work with our team of data scientists to automate the training and evaluation of models within an Azure ecosystem. This position will partner with many business, product and science teams, so written and in-person communication skills are extremely important. They must be comfortable working with a wide range of stakeholders and functional teams. The right candidate will have a passion for building complete engineering solutions supporting the latest advances in artificial technology. We have many different functions in the team, and this role requires a broad range of skills such as machine learning, data, optimization, and platform/infrastructure engineering.
Key Responsibilities
Study and transform data science prototypes
Design machine learning systems
Research and implement appropriate ML algorithms and tools
Design, build and run services at high scale and availability
Run machine learning tests and experiments
Train and retrain systems when necessary
Extend existing ML libraries and frameworks
Keep abreast of developments in the field
Demonstrates strong business acumen and understanding of manufacturing and finance concepts
Adept at quickly acquiring software skills
Evaluate new AI & software tools through POCs and propose solutions for implementation
Document guides, systems design, reference architectures and implementations
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