AI/ML Engineer, Burq

Salary not provided

+ Stock options and Performance-based Bonuses

React

AWS

Docker

TypeScript

Python

Tensorflow

Sagemaker

DynamoDB

Mid and Senior level

Remote from US

AI-powered last-mile delivery

Open for applications

AI-powered last-mile delivery

21-100 employees

B2BArtificial IntelligenceLogisticsDelivery

Open for applications

Salary not provided

+ Stock options and Performance-based Bonuses

React

AWS

Docker

TypeScript

Python

Tensorflow

Sagemaker

DynamoDB

Mid and Senior level

Remote from US

21-100 employees

B2BArtificial IntelligenceLogisticsDelivery

Company mission

To make offering delivery simple, flexible, and turnkey for enterprises.

Job

Company

Role

Who you are

3–6 years of professional experience in ML engineering, data science, or related roles
Hands-on experience with AWS services including SageMaker, Lambda, Step Functions, S3, and DynamoDB
Proficient in Python and ML frameworks such as TensorFlow
Proficient in Typescript and React to help bring AI/ML features into the product
Solid understanding of data engineering concepts: ETL, batch/streaming pipelines, and data validation
Familiar with containerization (Docker), CI/CD pipelines, and MLOps workflows
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

What the job involves

We’re growing fast and are looking for a AI/ML Engineer to help scale our platform, and help drive innovation in logistics and AI/ML-powered automation
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

Our take

For many B2C businesses, surviving today means meeting the on-demand delivery needs of consumers - something that can be difficult to achieve as a small business. Whilst last-mile delivery warehouses save small businesses from having to build their own delivery infrastructure, working exclusively with a single provider can greatly limit delivery options and stall a company's growth.

Burq provides an on-demand B2C delivery service platform which allows businesses to access multiple delivery providers for same-day delivery. The platform integrates directly with major sales platforms such as Zapier and Shopify, offering an analytic dashboard and delivery tracker across different modes of transport and providers.

Taking advantage of the expanding last-mile delivery sector, Burq has scaled its operations, swiftly building a thriving customer base in the small retailer and startup sectors. Having received funding from investors such as Village Global, it continues to launch new features and gain recognition as a partner for business growth.

Freddie

Company Specialist at Welcome to the Jungle

Company

Company HQ

SoMa, San Francisco, CA

Leadership

Salman Habib

(Co-Founder)

Previously co-founded HelpED Foundation where they served as the President. They also co-founded/ served as the CEO at Hellofriend.

Shaban Habib

(Co-Founder)

Co-founder of HelpED Foundation and Hellofriend. Previously co-founded Hilfe Billing Providers and worked in Business Data Management at SunTrust.

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