Benefits:
- Bonus based on performance
- Dental insurance
- Health insurance
- Vision insurance
Qualifications:
- 8+ years of software engineering and development experience
- Proven experience in building and deploying GenAI applications in production.
- Strong programming skills in Python and familiarity with GenAI libraries (Transformers, LangChain, Hugging Face, etc.).
- Deep understanding of LLMs, embeddings, vector databases (e.g., FAISS, Pinecone, Weaviate).
- Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
- Familiarity with CI/CD for ML workflows and versioning tools like MLflow or DVC.
- Hands-on experience designing and building cloud-native solutions (preferably on AWS)
- Exposure to GenAI tools and frameworks (e.g., LLMs, vector databases, prompt orchestration, LangChain, Bedrock)
- Familiarity with AWS AI/ML services (e.g., SageMaker, Bedrock, Comprehend, Lex)
- AWS AI certification
Responsibilities
- Design scalable and robust GenAI architectures using LLMs, multimodal models, and retrieval-augmented generation (RAG).
- Fine-tune foundation models using domain-specific data.
- Implement prompt engineering, instruction tuning, and reinforcement learning from human feedback (RLHF).
- Integrate GenAI capabilities into enterprise platforms using APIs, SDKs, and orchestration tools.
- Implement responsible AI practices including bias detection, hallucination mitigation, and explainability.
- Monitor and optimize model performance, latency, and cost.
- Use techniques like quantization, distillation, and caching to improve efficiency.
Tags & focus areas
Used for matching and alerts on DevFound Fulltime Ai Ai Engineer Machine Learning Generative Ai