AI/ML Engineer

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September 5

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Burq

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eCommerce • Logistics • SaaS

Burq is a comprehensive delivery platform that enables businesses across various industries, including e-commerce, food, floral, health & wellness, and construction, to offer on-demand delivery services. By integrating with Burq, companies can connect seamlessly with multiple delivery providers, allowing them to scale quickly to new markets and improve customer satisfaction with same-day and efficient delivery options. Burq also provides advanced tracking technology and does not charge commissions, ensuring optimal delivery solutions for businesses. With a focus on easy integration and a broad network of delivery providers, Burq empowers businesses to offer reliable delivery services without the need to build their own infrastructure.

11 - 50 employees

🛍️ eCommerce

☁️ SaaS

💰 Pre Seed Round on 2021-06

📋 Description

• 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

🏖️ Benefits

• Investing in you 🙏 • Competitive Salary, Stock Options, and Performance-based Bonuses • Fully Remote • Comprehensive Medical, Vision and Dental Insurance