AI/ML ENGINEER

TECH STACK: Python, SQL, Docker & Kubernetes, FastAPI, Flask, MLOps, Machine Learning, LLM's, LangChain or similar orchestrator, Vector DB or similar, GCP, Google AutoML, Vertex AI & Build tools


RESPONSIBILITIES:
• Design and implement scalable MLOps supportive data pipelines for data ingestion, processing, and storage.
• Experience deploying models with MLOps tools such as Vertex Pipelines, Kubeflow, or similar platforms.
• Experience implementing and supporting end-to-end Machine Learning workflows and patterns.
• Expert level programming skills in Python and experience with Data Science and ML packages and frameworks.
• Proficiency with containerization technologies (Docker, Kubernetes) and CI/CD practices.
• Experience working with large-scale machine learning frameworks such as TensorFlow, Caffe2, PyTorch, Spark ML, or related frameworks.
• Experience and knowledge in the most recent advancements in Gen AI, including Gemini, OpenAI, Claud and exposure to open-source Large Language Models (LLMs).
• Experience building AI/ML products using technologies such as LLMs, neural networks and others.
• Experience in building AI/ML Apps using Flask or FastAPI.
• Experience with RAG and Supervised Tuning techniques.
• Strong distributed systems skills and knowledge.
• Development experience of at least one public cloud provider, preferably GCP.
• Excellent analytical, written, and verbal communication skills.