Blue Ridge Solutions, Inc is looking to solve supply chain optimization problems using AI technology, specifically generative AI, to improve forecasting precision, reduce costs, and increase profit for distributors, retailers, and manufacturers.
Requirements
- 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
Responsibilities
- 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;
- Use Infrastructure as Code (IaC) to manage and version cloud resources for AI projects.
Other
- 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 foundation in statistics, linear algebra, and optimization techniques
- Experience with distributed systems and large-scale data processing
