Generative AI Developer

Role Descriptions: Key ResponsibilitiesGenerative AI Development Design and implement generative AI models for text| code| and multimodal applicationsLLM Engineering Fine-tune| optimize| and deploy large language models (GPT| Claude| Llama| etc.)Model Training Develop training pipelines for custom generative models and foundation model adaptationPython Development Build robust ML applications| APIs| and services using Python and ML frameworksPrompt Engineering Create and optimize prompts for various LLM applications and use casesModel Evaluation Implement evaluation frameworks for generative AI model performance and safetyProduction Deployment Deploy and monitor ML models in production environments with proper scalingResearch Innovation Stay current with latest GenAI research and implement state-of-the-art techniquesData Pipeline Management Build data preprocessing and feature engineering pipelines for ML workflowsCollaboration Work closely with product| engineering| and data science teams to deliver AI solutionsMust-haveStrong knowledge skills for GenAI| NLP and Machine learning| knowledge of data management.Proficiency in Python| ML frameworkslibraries like Langchain| TensorFlow| PyTorch| Hugging Face Transformers.Good knowledge of Public and Private cloud (Azure| AWS| OpenShift| Dockers| Kubernetes| ELK)| good understanding of microservice architecture.Experiences Database (SQL Server| Snowflake| SingleStore etc)Strong analytical| consultative| and team communication facilitative skillsNice-to-haveUnderstanding of IT Standards| Methodologies| CMM audit requirementsAgile experiences.Financial institution knowledge.
Essential Skills: Key ResponsibilitiesGenerative AI Development Design and implement generative AI models for text| code| and multimodal applicationsLLM Engineering Fine-tune| optimize| and deploy large language models (GPT| Claude| Llama| etc.)Model Training Develop training pipelines for custom generative models and foundation model adaptationPython Development Build robust ML applications| APIs| and services using Python and ML frameworksPrompt Engineering Create and optimize prompts for various LLM applications and use casesModel Evaluation Implement evaluation frameworks for generative AI model performance and safetyProduction Deployment Deploy and monitor ML models in production environments with proper scalingResearch Innovation Stay current with latest GenAI research and implement state-of-the-art techniquesData Pipeline Management Build data preprocessing and feature engineering pipelines for ML workflowsCollaboration Work closely with product| engineering| and data science teams to deliver AI solutionsMust-haveStrong knowledge skills for GenAI| NLP and Machine learning| knowledge of data management.Proficiency in Python| ML frameworkslibraries like Langchain| TensorFlow| PyTorch| Hugging Face Transformers.Good knowledge of Public and Private cloud (Azure| AWS| OpenShift| Dockers| Kubernetes| ELK)| good understanding of microservice architecture.Experiences Database (SQL Server| Snowflake| SingleStore etc)Strong analytical| consultative| and team communication facilitative skillsNice-to-haveUnderstanding of IT Standards| Methodologies| CMM audit requirementsAgile experiences.Financial institution knowledge.
Desirable Skills: