AI Systems Engineer

17 hours ago

Erode, Tamil Nadu, India beBeeDataDriven Full time ₹ 1,00,00,000 - ₹ 1,50,00,000

About Foodsmart:

We guide our members on a tailored journey to eating well while saving time and money through highly personalized digital platforms.

We seamlessly integrate dietary assessments and nutrition counseling with online food ordering and cost-effective meal planning for the entire family, optimizing ingredients both at home and on the go.

We partner with national and regional retailers across the U.S., many of whom accept SNAP/EBT, making healthier food more accessible. Additionally, we assist members with SNAP enrollment and management, providing tangible access to nutritious food.

We foster healthier food choices and drive lasting behavior change to deliver long-term health outcomes.

Our mission is to make nutritious food accessible and affordable for everyone, regardless of economic status. We are committed to a set of core values that shape our culture and work environment:

• Measured: We make data-driven, truth-seeking decisions.

• Impactful: We are fueled by achieving our mission and vision.

• Collaborative: We help each other be better and create a positive environment.

• Hungry: We maintain a healthy growth mindset, seeking to overcome challenges with courage.

• Joyful: We take joy in each other, our work, and the privilege of doing this work.

The AI Engineering team integrates intelligent systems across the member journey. From building conversational experiences and predictive models to optimizing outreach, the team plays a critical role in designing and deploying solutions.

You will:

  • Develop scalable backend applications using TypeScript, Node.js, and relational databases like PostgreSQL or MySQL.
  • Build and maintain APIs and microservices that enable real-time inference of AI/ML models.
  • Fine-tune pre-trained models for specific business use cases.
  • Integrate external AI services where appropriate.
  • Collaborate with cross-functional teams—ML engineers, software developers, product managers, and DevOps—to deliver end-to-end features.
  • Contribute to MLOps workflows, including deployment, versioning, and monitoring of models in production.
  • Follow engineering best practices for clean code, testing, observability, and reliability.

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