🕒 2 days ago
Lead product data science initiatives by building production machine-learning models, designing experiments, and translating analytics into product decisions and measurable business outcomes.
Data Science Lead - R01570347
📅 Aug 25
PythonSQLMachine LearningArtificial Intelligence
📜 Description
- Design and implement machine learning, LLM-based, and agentic AI solutions for complex business challenges.
- Lead deployment and operation of production AI/ML and GenAI models across Azure, AWS, or GCP.
- Build and optimize AI agents, autonomous workflows, and multi-agent architectures.
- Drive enterprise AI/ML workloads using Databricks AI Agents, Model Serving, Vector Search, MLflow, and Unity Catalog.
- Establish MLOps and LLMOps practices for CI/CD, model lifecycle management, evaluation, and monitoring.
- Develop RAG architectures and apply embeddings, vector databases, prompt engineering, and LLM evaluation; mentor engineers and collaborate across teams.
🛠️ Requirements
- Design and implement advanced machine learning and AI solutions, including LLM-based applications and agentic AI systems, to address complex business challenges and deliver measurable business outcomes
- Lead the development, deployment, and operation of production AI/ML and GenAI models across major cloud platforms such as Azure, AWS, or GCP, ensuring high availability and scalability
- Build, orchestrate, and optimize AI agents and autonomous workflows, focusing on robust memory, context management, and multi-agent architectures
- Drive enterprise AI/ML workloads within the Databricks ecosystem, leveraging Databricks AI Agents, Model Serving, Vector Search, MLflow, and Unity Catalog to enhance operational efficiency
- Establish and maintain MLOps and LLMOps practices, including CI/CD pipelines, model lifecycle management, experiment tracking, evaluation, and monitoring for continuous improvement
- Develop and apply RAG architectures, embeddings, vector databases, prompt engineering, and LLM evaluation frameworks to improve model performance and reliability
- Ensure AI security, responsible AI practices, data privacy, and effective mitigation of hallucination, prompt injection, and GenAI guardrails
- Mentor engineers and provide technical leadership, collaborating with cross-functional teams to deliver scalable, enterprise-grade AI solutions
- Advanced hands-on programming experience in Python
- Proficiency in SQL and experience with large-scale structured and unstructured datasets
Full job description
Data Science Lead
Job requirements
Experience Range: With at least 8 years of experience in AI/ML engineering, machine learning, data science, software engineering, or related fields Key Responsibilities:
Required Skills:
Preferred Skills:
Desired Qualifications:
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