Machine Learning Engineer

Recurring Decimal - Paradise Valley Village, AZ

Full-time

Paradise Valley Village, AZ

About the position

The Machine Learning Engineer role involves designing and implementing scalable MLOps data pipelines to support data ingestion, processing, and storage. The position requires expertise in deploying machine learning models using various MLOps tools and frameworks, as well as experience in building AI/ML products. The role emphasizes strong programming skills, particularly in Python, and familiarity with containerization technologies and cloud services.

Responsibilities

• Design and implement scalable MLOps supportive data pipelines for data ingestion, processing, and storage.
• Deploy models using MLOps tools such as Vertex Pipelines, Kubeflow, or similar platforms along with Vertex AI.
• Implement and support end-to-end Machine Learning workflows and patterns.
• Utilize LangChain or similar orchestrators and Vector DB or similar technologies.
• Develop AI/ML products using technologies such as LLMs and neural networks.
• Apply RAG and Supervised Tuning techniques in machine learning projects.
• Work with large-scale machine learning frameworks such as TensorFlow, Caffe2, PyTorch, or Spark ML.
• Collaborate with teams to ensure effective communication and project delivery.

Requirements

• Expert level programming skills in Python.
• 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, or Spark ML.
• Knowledge of recent advancements in Gen AI, including Gemini, OpenAI, and exposure to open-source Large Language Models (LLMs).
• Strong distributed systems skills and knowledge.
• Development experience with at least one public cloud provider, preferably GCP or Google AutoML.
• Excellent analytical, written, and verbal communication skills.