Burq

AI/ML Engineer

Burq

full-time

Posted on:

Origin:  • 🇺🇸 United States

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Job Level

Mid-LevelSenior

Tech Stack

AWSDockerDynamoDBETLPythonReactTensorflowTypeScript

About the role

  • Design, train, and deploy machine learning models using AWS-native tools (SageMaker, Lambda, Step Functions, S3)
  • Collaborate with data engineers to build and maintain robust data pipelines for feature ingestion, ETL, and model training
  • Fine-tune and optimize models for scalability, accuracy, and production readiness
  • Implement MLOps best practices including CI/CD pipelines, model versioning, monitoring, and automated retraining workflows
  • Monitor model performance, detect drift, and implement automated alerts and corrective actions
  • Work with cross-functional teams (product, software, infrastructure) to integrate AI capabilities into user-facing features
  • Share knowledge with the team through code reviews, documentation, and architecture discussions
  • Help scale Burq's platform and drive innovation in logistics and AI/ML-powered automation

Requirements

  • 3–6 years of professional experience in ML engineering, data science, or related roles
  • Design, train, and deploy machine learning models using AWS-native tools (SageMaker, Lambda, Step Functions, S3)
  • Hands-on experience with AWS services including SageMaker, Lambda, Step Functions, S3, and DynamoDB
  • Collaborate with data engineers to build and maintain robust data pipelines for feature ingestion, ETL, and model training
  • Proficient in Python and ML frameworks such as TensorFlow
  • Proficient in Typescript and React
  • Solid understanding of data engineering concepts: ETL, batch/streaming pipelines, and data validation
  • Familiar with containerization (Docker), CI/CD pipelines, and MLOps workflows
  • Implement MLOps best practices including CI/CD pipelines, model versioning, monitoring, and automated retraining workflows
  • Monitor model performance, detect drift, and implement automated alerts and corrective actions
  • Self-starter who thrives with autonomy and can deliver results with minimal oversight
  • Strong collaboration and communication skills; comfortable explaining ML concepts to technical and non-technical stakeholders
  • Bonus: AWS ML certification or equivalent hands-on experience
  • Bonus: Experience with generative AI, LLMs, or advanced ML applications