AI/ML Engineer

Burq

full-time

Posted on: 9/5/2025

Location: 🇺🇸 United States

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Mid-LevelSenior

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

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