Unspecified Salary Full Time
Machine Learning Engineer (Need from Payment card industry)
Job Description

Dice is the leading career destination for tech experts at every stage of their careers. Our client, Tekfortune Inc., is seeking the following. Apply via Dice today! Machine Learning Engineer - Phoenix, AZ (Onsite from day 1) (Need from Payment card industry) Key Responsibilities

- Architect And Design Machine Learning Solutions Using TensorFlow and PyTorch, Guiding the Development Process Through the Team to Ensure Product and Project Deliverables Align with Defined Scope and Standards. - Act As a Subject Matter Expert (SME) In Machine Learning, Providing Technical Guidance and Support to the Team and Stakeholders Throughout the Project Lifecycle. - Ensure Continuous Knowledge Enhancement by Exploring and Integrating New Technologies and Methodologies in Machine Learning, Maintaining the Relevance and Quality of Solutions Delivered to Clients. - Train And Mentor Team Members in Machine Learning Concepts and Tools, Fostering A Skilled Workforce That Effectively Mitigates Delivery Risks and Enhances Project Outcomes. - Gather Project Specifications and Deliver Tailored Machine Learning Solutions by Leveraging Domain Knowledge and Technical Expertise to Meet Client Requirements Effectively. - Review And Evaluate Project Deliverables, Ensuring They Meet Established Quality Criteria and Align with Industry Best Practices in Machine Learning. - Recommend And Implement Client Value Creation Initiatives by Applying Industry Best Practices in Machine Learning, Contributing to the Strategic Goals of the Organization.

Skill Requirements

- Expert Proficiency in Machine Learning Frameworks Such as TensorFlow and PyTorch. - Strong Programming Skills in Python, With A Good Understanding of Associated Libraries and Tools. - Solid Experience in SQL for Data Manipulation and Management. - In-Depth Knowledge of Machine Learning Algorithms and Model Development Processes. - Familiarity With Data Preprocessing, Feature Engineering, And Model Evaluation Techniques.