Lead AI/ML Developer

Description

Bid Lifecycle Assistant – a highly specialized solution designed to assist the Bid and Sales teams at key stages of the lifecycle of the bid process. This domain-specific solution employs various techniques such as multi-agent GenAI to provide support to the requirements and compliance process, data analysis and tender authoring process. The system is also to support data analytics to facilitate the analysis of trends across the bids in order to support Sales and Product Development teams. This system ensures seamless integration and efficient workflows while maintaining high standards of security and confidentiality.

#LI-IN1

Requirements

• Extensive experience in developing AI and machine learning models, with a focus on multi-agent systems and generative AI.
• Strong proficiency in programming languages such as Python, and familiarity with ML frameworks and libraries like TensorFlow, PyTorch, etc.
• Solid understanding of natural language processing techniques, with experience in deploying NLP systems and working with prompt libraries.
• Expertise in data analysis and analytics.
• Experience with cloud platforms for deploying AI solutions.
• Familiarity with DevOps practices and tools for CI/CD, containerization (Docker, Kubernetes), and version control (Git).
• Demonstrated experience in leading technical teams and managing complex projects from start to finish.
• Strong project management skills, with the ability to plan, execute, and oversee projects ensuring they meet deadlines and quality standards.
• Proven track record of driving innovation and solving complex technical problems using AI and machine learning.
• Excellent communication skills, with the ability to convey complex technical concepts to both technical and non-technical stakeholders.
• Experience working collaboratively within cross-functional teams.
• Understanding of data privacy and security standards, ensuring systems are compliant with industry regulations and best practices.
• Passion for continuous learning and staying updated with the latest trends and advancements in AI/ML technologies.

Job responsibilities

• Lead the design and development of AI/ML solutions, guiding other developers in implementing best practices.
• Oversee the entire development process from concept to deployment, ensuring alignment with project goals.
• Collaborate with solution architects to design scalable, maintainable, and efficient AI system architectures.
• Define technical strategies and roadmaps for implementing AI/ML functionalities in the system.
• Mentor and support the professional development of junior developers and engineers.
• Ensure optimal use of team skill sets and resources.
  Collaborate with stakeholders to understand the specific needs and requirements of the bid process lifecycle.
• Translate business needs into technical specifications for AI/ML models.
• Design and develop AI models, particularly multi-agent generative AI models, to assist with requirement compliance, data analysis, and tender authoring.
  Ensure models are trained on relevant datasets and are capable of providing accurate, context-aware insights.
• Implement NLP techniques to enable effective parsing and understanding of user prompts.
  Develop and refine the prompt library to facilitate seamless user interaction and request handling.
• Ensure the AI models integrate effectively with existing applications and workflows.
  Support the development of APIs or other integration methods to incorporate AI-generated data back into native applications.
• Develop analytics components to analyze trends across bids and provide actionable insights.
  Utilize statistical and machine learning techniques to derive patterns and predictions from historical data.
• Implement robust security measures to protect sensitive data and maintain confidentiality.
  Stay informed about the latest security protocols and ensure compliance with relevant regulations.
• Conduct thorough testing of AI models to ensure they meet quality, performance, and accuracy standards.
  Continuously evaluate model performance and implement improvements as necessary.
• Provide ongoing support and troubleshooting to address any system issues.
  Monitor and adapt AI systems to accommodate changes in the bid process or user requirements.
• Create comprehensive documentation for developed solutions.