Technology Specialist

Job Overview:

Perform product development from idea to prototype and further deployment. Apply knowledge and skills to complete varied assignments. Prioritize and organize own work to meet deadlines. Focus on completing work within schedule and budget. Clearly communicate and explain information in straightforward engineering activities.

Essential Qualifications and Education:

• 2-5 yrs in AI and ML development, with a proven track record of successful projects
• Bachelors or master s degree in computer science, Engineering, AI, Mathematics, or a related field
• Familiar with the content and application of standards, codes and guidelines as applicable. Knowledge of many basic design techniques and analysis methods.
• Deep understanding of data structures, algorithms, and statistical methods or front- end development
• Strong proficiency in programming languages such as Python, Java, or other relevant programming languages
• Expertise in machine learning frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., scikit-learn, pandas)
• Experience with cloud platforms like Azure ML is preferred
• Published research or contributions to open-source projects in the AI/ML field is preferred
• Advanced knowledge of specialized areas like deep learning, natural language processing, or computer vision
• Strong analytical and problem-solving skills
• Excellent communication and teamwork abilities
• Familiar with the content and application of standards, codes and guidelines as applicable
• Knowledge of many basic design techniques and analysis methods

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Key Tasks and Responsibilities:

• Perform product development from idea to prototype and further deployment.
• Apply knowledge and skills to complete varied assignments.
• Prioritize and organize own work to meet deadlines.
• Focus on completing work within schedule and budget.
• Clearly communicate and explain information in straightforward engineering activities.
• Lead the development and implementation of complex machine learning models, ensuring they meet project requirements and performance metrics
• Oversee data preprocessing, cleansing, and management. Develop strategies for data acquisition and utilization to enhance model performance
• Optimize existing AI/ML models for better efficiency and accuracy. Implement advanced algorithms and techniques to improve system performance
• Work closely with various teams, including data scientists, domain engineers, and product managers, to integrate AI/ML solutions into products and services. Act as a liaison between technical and non-technical teams to facilitate effective communication
• Provide guidance and mentorship to junior team members. Lead project teams as required, ensuring timely delivery and quality of work
• Engage in ongoing research to stay ahead of the latest trends and developments in AI and ML. Propose and lead innovative projects or experiments
• Prepare comprehensive documentation and reports on AI/ML projects, including development processes, performance metrics, and deployment strategies
• Assist in the Integration of models into systems:
  • Collaborate with software engineers and IT teams to seamlessly incorporate machine learning models into production environments.
  • Design and develop APIs or interfaces for model integration, ensuring compatibility with existing systems
  • Optimize model performance for real-time or batch processing as required by the application
  • Develop automated workflows for model training, testing, and deployment to streamline the integration process