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As a Python, AI/ML, and Generative AI Developer, you will be responsible for end-to-end ownership of designing, developing, validating, and automating solutions for the automation team. You will leverage your expertise in Python, AI/ML frameworks, and Generative AI technologies to deliver scalable, efficient, and innovative solutions. This role requires hands-on experience and the ability to work across the entire development lifecycle, including requirement gathering, design, implementation, testing, and deployment.
Job Responsibility:
Take full ownership of designing and developing AI/ML and Generative AI solutions to automate business processes
Architect and implement scalable, efficient, and maintainable solutions using Python and relevant AI/ML frameworks
Develop and fine-tune Generative AI models (e.g., GPT, LangChain, Hugging Face) for specific use cases
Design and implement APIs and integrations to connect AI/ML solutions with existing systems
Build, train, and validate machine learning models, ensuring high accuracy and performance
Develop Generative AI models for tasks such as text generation, classification, summarization, and more
Perform data preprocessing, feature engineering, and model optimization to improve outcomes
Validate models through rigorous testing and ensure compliance with business requirements
Automate repetitive tasks and workflows using Python scripts and AI/ML models
Implement end-to-end automation pipelines, including data ingestion, model training, validation, and deployment
Optimize existing automation solutions for performance, scalability, and reliability
Collaborate with cross-functional teams, including data scientists, business analysts, and operations teams, to gather requirements and deliver solutions
Partner with stakeholders to identify automation opportunities and propose AI/ML-driven solutions
Communicate technical concepts and project updates effectively to non-technical stakeholders
Develop and execute test cases to validate AI/ML models and automation workflows
Ensure solutions meet quality standards and adhere to best practices in software development
Implement automated testing frameworks to streamline validation processes
Deploy AI/ML models and automation solutions into production environments
Monitor the performance of deployed solutions and address any issues proactively
Implement logging, monitoring, and alerting mechanisms to ensure system reliability
Stay updated on the latest advancements in Python, AI/ML, and Generative AI technologies
Experiment with new tools, frameworks, and methodologies to enhance automation capabilities
Propose innovative solutions to improve efficiency and reduce manual effort
Create and maintain detailed documentation for all solutions, including design, implementation, and testing
Share knowledge and mentor junior team members to build technical expertise within the team
Requirements:
Strong expertise in Python, with experience in developing scalable and maintainable code
Hands-on experience with TensorFlow, PyTorch, Scikit-learn, or similar frameworks
Proficiency in tools like OpenAI GPT, LangChain, Hugging Face, or similar platforms
Experience in building end-to-end automation pipelines and integrating AI/ML solutions into workflows
Strong knowledge of data preprocessing, feature engineering, and working with structured/unstructured data
Experience in designing and implementing RESTful APIs and integrating AI/ML solutions with existing systems
Proficiency in developing test cases and implementing automated testing frameworks
Familiarity with cloud platforms like AWS, Azure, or GCP for deploying AI/ML solutions
Experience with Git and CI/CD pipelines for version control and deployment
Strong problem-solving skills, attention to detail, and the ability to work independently and collaboratively
8 years of relevant experience
Experience in systems analysis and programming of software applications
Experience in managing and implementing successful projects
Working knowledge of consulting/project management techniques/methods
Ability to work under pressure and manage deadlines or unexpected changes in expectations or requirements
Bachelor’s degree/University degree or equivalent experience
Nice to have:
Experience with vector databases (e.g., Pinecone, FAISS) and knowledge graphs
Familiarity with MLOps practices for managing the AI/ML lifecycle
Knowledge of Agile methodologies and tools like JIRA or Confluence
Prior experience in mentoring or leading junior developers