Specialist - Data Sciences Job Irving area,Texas USA,Software Development

Design develop and deploy MLAI models for real time and batch use cases including model experimentation training and evaluation
Build and optimize inference pipelines and integrate ML capabilities into applications services in partnership with product and engineering teams
Develop and maintain data pipelines for model training validation and continuous improvement retraining continual learning
Monitor model performance in production quality drift bias hallucinations where applicable and drive improvements in reliability and robustness
Establish engineering best practices for ML delivery reproducibility versioning testing documentation and benchmarking experimentation
Contribute to solution architecture decisions for ML systems data compute deployment patterns and operational controls
Mentor junior engineers and lead technical reviews for ML code pipelines and deployment implementations 712 years of experience in software engineering data engineering ML engineering with significant hands on time delivering ML solutions
Strong proficiency in Python and MLDL libraries such as PyTorch Tensor Flow and familiarity with modern model ecosystems eg Hugging Face
Solid understanding of ML fundamentals feature engineering model selection evaluation metrics overfitting cross validation and deep learning concepts neural nets transformers where relevant
Experience with model deployment approaches tools eg model serving ONNX Torch Serve Triton or equivalent
Strong engineering practices clean code debugging performance optimization API integration and collaboration in cross functional teams
Experience with MLOps GenAIOps tooling such as MLflow containerization Docker and cloud platforms AWS, Azure, GCP for scalable ML delivery Experience with LLMs Generative AI fine tuning prompt engineering evaluation and production patterns
Familiarity with RAG and vector databases plus responsible ethical AI practices and governance
Experience building automated benchmarking AB testing and monitoring frameworks for ML systems
Contributions to open source publications patents or strong internal innovation track record Strong ownership and ability to lead quality outcomes end-to-end
Clear communication and stakeholder management

Role Description

Title:

Gen AI Engineer Location Irving, Tx (Hybrid)

Design develop and deploy MLAI models for real time and batch use cases including model experimentation training and evaluation
Build and optimize inference pipelines and integrate ML capabilities into applications services in partnership with product and engineering teams
Develop and maintain data pipelines for model training validation and continuous improvement retraining continual learning
Monitor model performance in production quality drift bias hallucinations where applicable and drive improvements in reliability and robustness
Establish engineering best practices for ML delivery reproducibility versioning testing documentation and benchmarking experimentation
Contribute to solution architecture decisions for ML systems data compute deployment patterns and operational controls
Mentor junior engineers and lead technical reviews for ML code pipelines and deployment implementations 712 years of experience in software engineering data engineering ML engineering with significant hands on time delivering ML solutions
Strong proficiency in Python and MLDL libraries such as PyTorch Tensor Flow and familiarity with modern model ecosystems eg Hugging Face
Solid understanding of ML fundamentals feature engineering model selection evaluation metrics overfitting cross validation and deep learning concepts neural nets transformers where relevant
Experience with model deployment approaches tools eg model serving ONNX Torch Serve Triton or equivalent
Strong engineering practices clean code debugging performance optimization API integration and collaboration in cross functional teams
Experience with MLOps GenAIOps tooling such as MLflow containerization Docker and cloud platforms AWS, Azure, GCP for scalable ML delivery Experience with LLMs Generative AI fine tuning prompt engineering evaluation and production patterns
Familiarity with RAG and vector databases plus…