Sr AIML Architect - Austin TX DAY 1 onsite - Contract

Job title: AI/ML Architect

Job location: Austin TX (Onsite)

Job type: Contract

Job Description:

• Proficiency in common ML programming languages such as Python and experience with relevant libraries & frameworks like Scikitlearn TensorFlow and PyTorch.
• Strong working knowledge of cloudbased Machine Learning platforms like AWS SageMaker Azure ML etc.
• Strong understanding of machine learning algorithms including supervised and unsupervised learning deep learning and reinforcement learning with the ability to build deploy and manage models.
• Expertise in the design and implementation of machine learning models including evaluating performance and finetuning parameters for optimal results.
• Knowledge of statistical concepts and methodologies to ensure reliable and accurate model development and validation.
• Handson experience with technologies available in the marketplace related to Conversation Bots and adoption.
• Ability to analyze large datasets and apply data preprocessing techniques feature engineering and dimensionality reduction.
• Familiarity with cloud computing platforms and distributed computing frameworks for scalable and efficient model training and deployment (e.g. AWS GCP Azure).
• Familiarity with GenAI environments like Azure OpenAI AWS Bedrock etc. and Large Language Models (LLM).
• Experience on langgraph crewai & langchain is an advanatage.
• Experience on implementing graph algorithms for the business problem statement is preferred
• Strong problemsolving and critical thinking skills with the ability to identify business challenges and apply appropriate machine learning techniques to address them.
• Experience in working with structured and unstructured data including text and time series data and the ability to develop custom models for specific data types. Excellent communication skills with the ability to convey complex technical concepts to both technical and nontechnical stakeholders.
• Continuous learning mindset and staying uptodate with the latest advancements in machine learning and engaging with the research community.