- Generative AI Expertise Good understanding of various Generative AI techniques including GANs VAEs and other relevant architectures
- Proven experience in applying these techniques to real world problems for tasks such as image and text generation
- Conversant with Gen AI development tools like Prompt engineering Langchain Semantic Kernels Function calling
- Exposure to both API based and opens source LLMs based solution design
- Technical Proficiency An overall understanding of below technologies is required
- Machine learning algorithms Linear regression logistic regression decision trees random forests support vector machines neural networks
- Data science tools NumPy SciPy Pandas Matplotlib TensorFlow Keras
- Cloud computing platforms AWS Azure GCP
- Natural language processing NLP Transformer models attention mechanisms word embeddings
- Computer vision Convolutional neural networks recurrent neural networks object detection
- Robotics Reinforcement learning motion planning control systems
- Data ethics Bias in machine learning fairness in algorithms
Key Responsibilities:
- Robust Python proficiency with experience in FastAPI asyncio modular application design and parallel processing
- Develop scalable and modular Python applications for deploying generative AI solutions
- Build and manage cloud infrastructure using AWS services S3 Lambda DynamoDB ECS EKS
- Automate infrastructure provisioning and configuration using Terraform
- Collaborate with data scientists ML engineers and product teams to integrate AI models into domain specific applications
- Ensure production grade scalability reliability and security of GenAI systems
- Monitor and optimize system performance using tools like AWS CloudWatch
- Stay updated with advancements in GenAI cloud computing MLOps and DevOps
- Contribute to code reviews documentation and Python development best practices
Technical Requirements:
- Familiarity with Python parallel processing modules such as multiprocessing concurrent
- futures dask for efficient parallel and distributed computing
- Hands on experience with GenAI frameworks such as LangChain LangGraph and Prompt Engineering
- Proficient in AWS cloud services and cloud native architecture
- Skilled in Infrastructure as Code IaC using Terraform
- Familiar with CI CD pipelines Docker and Kubernetes
- Familiarity with code quality tools such as pylint black isort mypy pytest SonarQube SonarLint and Black Duck for linting formatting testing static analysis and open source security compliance
- Solid understanding of security best practices in cloud and AI deployments