Blue Ridge

Lead Full-Stack Engineer, GenAI

Blue Ridge

full-time

Posted on:

Origin:  • 🇺🇸 United States

Visit company website
✨ AI Apply
Manual Apply

Job Level

Senior

Tech Stack

ApacheCloudDistributed SystemsDockerERPJavaScriptKerasKubernetesMicroservicesNode.jsOpen SourcePythonPyTorchReactScikit-LearnSparkSQLTensorflowTypeScript

About the role

  • Design and develop Generative AI solutions using cloud-based managed AI services (e.g. Amazon Bedrock, Amazon SageMaker).
  • Design and develop AI Agent workflows using cloud and open source agentic frameworks.
  • Containerize AI applications and deploy them using cloud orchestration services.
  • Collaborate with data architects/engineers to build end-to-end AI pipelines.
  • Implement MLOps practices to automate the development, deployment, and monitoring of AI applications and models.
  • Implement and manage robust monitoring systems for AI solutions in production environments, ensuring continuous performance tracking, anomaly detection, and model drift analysis; collaborate with cross-functional teams to deploy model updates, maintain version control, and optimize model efficiency over time.
  • Use Infrastructure as Code (IaC) to manage and version cloud resources for AI projects.
  • Ensure clear and accessible knowledge transfer to internal teams and create knowledge-sharing resources to ensure smooth transitions during model handoffs and system updates.
  • Contribute to the development of best practices and standards for AI engineering within the organization.
  • Lead the architecture and implementation of ML systems that can process supply chain data at scale
  • Research and implement cutting-edge ML techniques including transformer models, reinforcement learning, and generative adversarial networks
  • Optimize model performance for production environments, ensuring low latency and high availability
  • Establish best practices for model versioning, monitoring, and continuous integration/deployment
  • Understand critical supply chain planning workflows and identify opportunities for AI-driven automation
  • Develop ML models that provide insights into potential supply disruptions and recommend automated resolutions
  • Build tools that increase the reach of supply chain solutions through partner integrations
  • Act as the voice of AI innovation within the supply chain domain.

Requirements

  • University degree or higher in Computer Science, Machine Learning, Data Science, Artificial Intelligence, or related technical field, OR 5-7 years of equivalent experience in machine learning engineering
  • 3+ years of hands-on experience designing, building, and deploying ML models and systems in production environments
  • 3+ years of experience with deep learning frameworks (PyTorch, TensorFlow, Keras) and generative AI models
  • Strong full-stack development experience with modern web technologies, ability to take concept to prototype
  • Programming Languages: Expert-level proficiency in Python; proficiency in JavaScript/TypeScript, SQL
  • ML/AI Frameworks: PyTorch, TensorFlow, Hugging Face Transformers, LangChain, scikit-learn or equivalent
  • Generative AI: Experience with large language models (GPT, BERT, LLaMA), fine-tuning techniques (RLHF, LoRA), and prompt engineering or equivalent
  • Full-Stack Development: React, Node.js, REST APIs, microservices architecture
  • MLOps: Docker, Kubernetes, CI/CD pipelines, model monitoring, and deployment automation or equivalent
  • Data Technologies: Apache Spark, streaming data processing, vector databases, data warehousing or equivalent
  • Strong foundation in statistics, linear algebra, and optimization techniques
  • Experience with distributed systems and large-scale data processing
  • Proficiency in data structures, algorithms, and software engineering principles
  • Experience with A/B testing, model evaluation, and performance monitoring