Senior AI Lead, Location: Fort Mill, SC/ Princeton, NJ

Title: Senior AI Lead

Location:  Fort Mill, SC/ Princeton, NJ

Type : Contract for 12 months

Visa : OPT/CPT

Exp : 10 years

 

Job Description

Candidates should have experience with AI LLM (Large Language Models).

Responsibilities:

 

    Lead AI Strategy and Roadmap: Define the AI strategy, aligning it with business goals, and identify key areas where AI can create value for the organization.

    Oversee AI Solution Development: Guide the development and implementation of AI models, including machine learning, NLP, computer vision, and predictive analytics, ensuring solutions are robust, scalable, and aligned with requirements.

    Collaborate with Cross-Functional Teams: Work closely with product managers, data engineers, and software developers to integrate AI solutions into products and services.

    Ensure Model Quality and Accuracy: Establish best practices for model development, testing, and validation to ensure high-quality AI solutions, with a focus on accuracy, reliability, and bias mitigation.

    Data Management and Pre-processing: Oversee data sourcing, pre-processing, and feature engineering to ensure the quality and readiness of data used for AI models.

 

Skills Required:

 

    Experience: 3+ years of experience in AI, machine learning, or data science, with a proven track record of deploying AI solutions in a production environment.

    Technical Expertise: Deep understanding of AI and machine learning techniques, including supervised and unsupervised learning, NLP, computer vision, deep learning, and statistical modeling.

    Proficiency in AI Tools and Frameworks: Strong experience with AI and machine learning frameworks such as TensorFlow, PyTorch, Scikit-Learn, and cloud-based ML services (e.g., AWS SageMaker, Azure ML, Google AI).

    Programming Skills: Proficiency in programming languages like Python and familiarity with data processing libraries (e.g., Pandas, NumPy).

    Data Management Knowledge: Experience with big data technologies (e.g., Hadoop, Spark) and data engineering best practices.

    Strategic and Analytical Thinking: Ability to develop AI strategies aligned with business goals and assess the business impact of AI initiatives.

    Communication and Collaboration: Excellent communication skills to work effectively with cross-functional teams and to present complex technical information to non-technical stakeholders.


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