CloudDockerETLGoogle Cloud PlatformKubernetesPythonPyTorchScikit-LearnSQLTensorflowAIMachine LearningMLNLPLLMLarge Language ModelsRAGAgenticTensorFlowscikit-learnELTGCPGoogle CloudCI/CD
About this role
Role Overview
Work closely with stakeholders and software engineers to identify and design high-impact AI solutions, including RAG/Agentic-based applications, ETL pipelines that leverage LLMs to extract key insights/enhance data
Leverage traditional machine learning, NLP techniques, and Large Language Models (LLMs) to analyze notes, transcripts and other unstructured text data
Develop models for tasks such as topic modeling, classification, sentiment analysis, entity extraction, and error detection
Establish robust evaluation frameworks (precision, recall, F1) and conduct iterative error analysis to continuously improve performance and reliability
Design and build LLM-powered applications and services to assist technicians
Apply best practices in prompt engineering (Chain-of-Thought, few-shot prompting, structured outputs), Retrieval-Augmented Generation (RAG), and agentic systems (tool usage, multi-step reasoning, API chaining, stateful workflows)
Implement guardrails, validation layers, and hallucination mitigation strategies
Architect, develop, and deploy scalable AI-powered APIs, applications and automated workflows
Make deliberate design tradeoffs balancing latency, cost, performance, reliability, and lifecycle ownership
Build modular, maintainable systems that integrate seamlessly with enterprise data sources and operational platforms
Implement CI/CD pipelines for deployments
Manage infrastructure using Infrastructure as Code (IaC), containerize services, and deploy to Kubernetes
Establish monitoring, logging, versioning, and rollback strategies to ensure reliability, observability, and scalability in production
Partner with engineering, operations, and business stakeholders to translate real-world challenges into AI solutions
Clearly document architectural decisions and learnings
Mentor team members and contribute to a culture of technical excellence
Requirements
Master’s degree in Computer Science, Machine Learning, Data Science, Statistics, or a related quantitative discipline — or a PhD in a relevant field
3+ years of experience applying machine learning and AI in production environments, delivering measurable business impact
Strong foundation in traditional ML and NLP (classification, regression, clustering, topic modeling, sentiment analysis) with experience designing robust evaluation frameworks (precision/recall/F1, experimentation, error analysis)
Practical experience working with LLMs, including prompt engineering, structured outputs, and building Retrieval-Augmented Generation (RAG) systems
Experience designing and implementing agentic AI systems, including multi-step reasoning workflows, tool/API orchestration, memory/state management, and production guardrails
Experience building AI-powered applications and APIs, with an understanding of latency, scalability, cost optimization, and reliability tradeoffs
Proficiency in Python and modern ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn), and experience developing and consuming REST APIs
Experience building data pipelines (ETL/ELT), preprocessing structured and unstructured data, and strong SQL skills working with large-scale datasets
Experience deploying models using Docker and Kubernetes, with familiarity in CI/CD, cloud platforms (GCP) and production monitoring
Strong ability to translate ambiguous business problems into scalable AI systems and communicate effectively with both technical and non-technical stakeholders.
Tech Stack
Cloud
Docker
ETL
Google Cloud Platform
Kubernetes
Python
PyTorch
Scikit-Learn
SQL
Tensorflow
Benefits
Comprehensive total rewards package highlighting competitive salary and bonus structures
Minimum 3 weeks of vacation
Flexible benefits plan to meet the needs of you and your family
Generous company matched pension and share purchase programs
Opportunity to give back to communities in which we work, live and serve
Career growth and learning & development opportunities to develop your skills