Key Responsibilities:
* AI/GenAI Solution Design – Architect and implement AI/GenAI solutions for public and private cloud environments (AWS, Azure, GCP).
* Model Development – Fine-tune, train, and optimize LLMs and ML models for industry-specific use cases.
* Pipeline Engineering – Build robust data ingestion, preprocessing, and feature engineering pipelines.
* Integration & APIs – Develop secure, scalable APIs and SDKs for embedding AI into enterprise systems.
* Performance Optimization – Monitor, evaluate, and enhance AI models for accuracy, latency, and cost efficiency.
* Security & Compliance – Ensure AI solutions meet enterprise-grade security, privacy, and compliance requirements.
* Collaboration – Partner with product managers, solution architects, the CDIO, and CEO to deliver high-impact solutions.
* Innovation – Stay ahead of AI trends, evaluating new technologies to continuously evolve Simplify's AI capabilities.
Required Skills & Experience:
* Bachelor's/Master's in Computer Science, AI/ML, Data Science, or related field.
* 1-2 years in AI/ML engineering, including 1+ year working with LLMs and GenAI.
* Proficiency in Python with experience in PyTorch, TensorFlow, Hugging Face Transformers, LangChain, LlamaIndex, etc.
* Expertise in RAG (Retrieval-Augmented Generation) and vector databases (Pinecone, Weaviate, FAISS, Milvus).
* Strong understanding of cloud AI services (AWS Bedrock/SageMaker, Azure OpenAI, Google Vertex AI).
* Experience with ML Ops frameworks and CI/CD for AI pipelines.
* Familiarity with enterprise integration (REST APIs, gRPC, message brokers, microservices).
* Strong problem-solving, analytical, and communication skills.
* Proven experience fine-tuning LLMs for domain-specific applications.