Job Description -

AI/ML Architect

Job Title: AI/ML Architect

Location: Tampa FL Onsite

Duration: Long Term

VISA : & GCEAD

Active LinkedIn

Full Education details

Required Skills

NLP with GenAI (OpenAI, LLaMa models)

AI/ML algorithms and models

Computer vision / OCR

Azure AI skills

Python

TensorFlow

PyTorch

Job Description:

Position Summary:

As an AI/ML Architect, you will play a crucial role in designing and implementing robust, scalable, and efficient AI/ML solutions for our diverse range of projects. The successful candidate will be responsible for understanding business requirements, defining architecture, and leading the development of AI/ML models that drive innovation and enhance business outcomes.

Responsibilities

Collaborate with cross-functional teams to understand business objectives and requirements.

Design end-to-end AI/ML architectures that align with business goals and scalability requirements.

Evaluate and select appropriate technologies and frameworks for implementation.

Lead the development and implementation of state-of-the-art AI/ML models.

Utilize Python and other relevant tools to build and optimize machine learning algorithms.

Ensure models are accurate, efficient, and scalable for deployment in production environments.

Work closely with data engineers to ensure the availability of high-quality, clean, and relevant data.

Develop and implement data preprocessing and feature engineering pipelines.

Implement monitoring systems to track the performance of deployed models.

Identify opportunities for optimization and improvement in model accuracy and efficiency.

Collaborate with cross-functional teams, including data scientists, engineers, and business stakeholders.

Document architecture, design decisions, and code to ensure knowledge transfer and maintainability.

Qualifications:

Master's or Ph.D. in Computer Science, Data Science, or related field.

Proven experience as an AI/ML Architect with a focus on Python-based solutions.

Strong expertise in machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn.

Experience with designing and implementing end-to-end machine learning pipelines.

Proficiency in data processing, feature engineering, and model deployment.

Excellent communication skills and the ability to collaborate effectively with cross-functional teams.

Demonstrated problem-solving and critical-thinking skills.

Preferred Skills

Experience with cloud platforms such as AWS, Azure, or Google Cloud.

Knowledge of containerization technologies (Docker, Kubernetes).

Familiarity with deep learning techniques and frameworks