ML Architect / ML Lead /Senior ML (Dallas, TX/Basking Ridge, NJ) at Infinite Computer Solutions Inc

Key Responsibilities:

• Model Development:
• Collaborate with data scientists to develop, train, and validate machine learning models.
• Implement algorithms and techniques suitable for real-time data processing and inference.
• Real-Time Deployment:
• Design and implement robust deployment pipelines for machine learning models in real-time environments.
• Utilize cloud services (Google Cloud Platform or AWS) for deploying and scaling machine learning models.
• System Architecture:
• Architect and optimize end-to-end machine learning solutions that integrate seamlessly with existing infrastructure.
• Ensure solutions are built for scalability, maintainability, and high availability.
• Performance Monitoring:
• Monitor model performance and ensure real-time systems are operating at optimal levels.
• Implement logging, tracking, and alerting mechanisms to identify and address model drift or system failures.
• Collaboration:
• Work closely with cross-functional teams, including data engineers, software developers, and product managers, to align on project goals and deliverables.
• Communicate technical concepts to non-technical stakeholders effectively.
• Documentation:
• Create and maintain documentation for model development, deployment processes, and system architecture.
• Document best practices and contribute to knowledge-sharing initiatives within the team.
• Continuous Improvement:
• Stay up-to-date with the latest trends in machine learning and cloud technologies.
• Proactively identify areas for improvement in existing processes and models.

Qualifications:

Education:

• Bachelor s degree in Computer Science, Data Science, Mathematics, or a related field. Master s degree preferred.

Experience:

• 3+ years of experience in machine learning engineering, data science, or related fields.
• Proven experience with real-time model deployment on cloud platforms (AWS, Google Cloud Platform).
• Familiarity with tools like TensorFlow, PyTorch, Scikit-learn, or similar libraries.

Technical Skills:

• Proficient in programming languages such as Python, Java, or Scala.
• Strong understanding of data structures, algorithms, and machine learning concepts.
• Experience with containerization technologies (Docker, Kubernetes) for model deployment.
• Knowledge of cloud services like AWS SageMaker, Google AI Platform, or similar.

Soft Skills:

• Strong analytical and problem-solving skills.
• Excellent communication skills, with the ability to articulate complex ideas to diverse audiences.
• Ability to work in a fast-paced, agile environment and manage multiple priorities.