AI Engineer

Avid Technology Professionals

Maryland

Sur place

USD 90 000 - 120 000

Plein temps

14 jours+
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Résumé du poste

A leading technology company in Maryland is seeking an experienced professional to lead the design and development of AI-driven solutions. You will collaborate with cross-functional teams to interpret and recommend AI approaches, conduct data analysis, and develop machine learning models. This role requires expertise in AWS and continuous improvement of AI systems. Ideal candidates will have experience in model evaluation and a strong capacity for both technical and non-technical communication.

Qualifications

  • Experience in designing and developing AI solutions from conception to deployment.
  • Ability to work collaboratively with technical and non-technical teams.
  • Strong skills in conducting data analysis and model evaluation.

Responsabilités

  • Lead design and development of AI-driven solutions.
  • Collaborate with cross-functional teams to refine AI approaches.
  • Conduct Exploratory Data Analysis on diverse datasets.
  • Develop, train, and evaluate machine learning models.

Connaissances

AI-driven solutions development
Cross-functional collaboration
Data analysis
Model building and evaluation
AWS and MLOps tools

Description du poste

Design and Development: Lead the design and development of AI-driven solutions from conception to deployment, ensuring seamless integration with the existing software architecture. This includes prototyping new models, writing production-quality code, and maintaining existing AI systems.

Collaboration and Communication: Serve as a key technical liaison, collaborating with cross‑functional teams including system engineers, software developers, and domain experts. Effectively present and articulate recommended AI approaches, discussing the tradeoffs and implications of different implementations with both technical and nontechnical stakeholders.

Data Analysis and Modeling: Conduct Exploratory Data Analysis (EDA) on diverse datasets (both structured and unstructured) to inform the data model, identify data quality issues, and determine optimal input formats for AI models.

Model Building and Evaluation: Develop, train, and evaluate a variety of machine learning models, ensuring they meet performance and reliability requirements. Implement robust testing and validation strategies to ensure models are accurate and unbiased. Continuous Improvement: Stay current with the latest advancements in AI and machine learning, continuously seeking opportunities to apply new technologies and methodologies to improve existing systems and solve complex problems. Cloud Platforms: Have experience with the Amazon Web Services (AWS) cloud computing platform and machine learning operations (MLOps) tools for deploying and managing machine learning models at scale.

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