AI/ML Engineer - Generative AI

AI/ML Engineer

Key Responsibilities:

AI Build Plan Development:

• Conduct in-depth analysis of business requirements and identify strategic AI/ML opportunities to drive growth and efficiency.
• Develop a comprehensive AI build plan, outlining strategic objectives, technology roadmap, and resource allocation.
• Prioritize AI initiatives based on business impact, feasibility, and ROI.
• Collaborate with cross-functional teams to align AI strategy with overall business goals.

AI Investment Strategy:

• Define AI investment criteria and evaluate potential AI projects for funding.
• Develop financial models to assess the ROI of AI initiatives and justify investments.
• Manage AI budget allocation and track spending against the approved plan.

AI Team Leadership (Implicit for a Lead Role):

• Build and lead a high-performing AI team of data scientists, machine learning engineers, and other AI professionals.
• Provide technical guidance and mentorship to team members.
• Foster a culture of innovation and experimentation within the AI team.

AI Model Development and Deployment:

• Oversee the development and deployment of

  AI models

  , with a specific focus on

  Generative AI models

  , across various business domains.
• Ensure the quality, accuracy, and scalability of AI models.
• Monitor model performance and implement necessary improvements and optimizations.

Technology Evaluation and Adoption:

• Stay up-to-date with the latest advancements in

  AI/ML technologies

  , particularly in Generative AI.
• Evaluate new AI tools and platforms to identify potential benefits for the organization.
• Drive the adoption of cutting-edge AI technologies across the enterprise.

Required Qualifications:

• Strong proficiency in

  Python, C++

  , and deep learning frameworks such as

  Keras, TensorFlow, PyTorch

  , etc.
• Extensive experience in

  machine learning algorithms

  (e.g., CNNs, RNNs, LSTMs, Seq2seq) and neural network architectures.
• Proven ability to create and optimize

  AI models

  for various use cases, with a focus on Generative AI applications.
• Deep understanding of performance and accuracy metrics for different AI models.
• Experience with

  AI model optimization for CPUs and GPUs

  .
• Knowledge of machine learning accelerators and related software.
• Excellent communication and interpersonal skills.
• Strong analytical and problem-solving abilities.
• Experience with open-source tools for AI model optimization (e.g., TF/ONNX/PyTorch).
• Demonstrated exposure to

  Generative AI technologies

  and their potential applications.

Preferred Qualifications:

• Experience in leading AI projects from inception to deployment.
• Knowledge of major

  cloud platforms (AWS, Azure, GCP)

  .
• Experience with

  big data technologies and tools

  .
• A Master's or Ph.D. degree in computer science, statistics, or a related field.