ML Engineer, Business Intelligence

Develop and maintain backend systems for Foodsmart web application

Collaborate with front-end engineers to design APIs

Analyze threat actor behavior across datasets

Implement state-of-the-art techniques for abuse detection

Develop state-of-the-art voice cloning technology

Implement low latency and cost-effective text-to-speech solutions

Design, build, and maintain scalable distributed backend systems

Work closely with product and engineering peers

Analyze threat actor behavior and evolving abuse patterns

Research and implement state-of-the-art abuse detection techniques

Develop and deploy AI models

Create low-latency text-to-speech solutions

Design, build, and maintain scalable distributed backend systems

Work closely with product and engineering peers to shape product decisions

Design, build, and maintain scalable distributed backend systems

Work closely with product and engineering peers

Contribute to cutting-edge voice cloning and text-to-speech technologies.

Utilize backend development skills in Python for efficient applications.

Analyze threat actor behavior and abuse patterns

Design and develop production-ready systems for abuse detection

Analyze threat actor behavior and evolving abuse patterns

Research and implement AI-driven techniques for abuse detection

Design, build, and maintain scalable distributed backend systems

Work closely with product and engineering peers

Develop low latency and cost-effective voice cloning and text to speech using AI models.

Prioritize tasks based on urgency and impact for efficient implementation.

Design, build, and deliver platform features

Own full lifecycle from design to deployment

Architect scalable automated test frameworks using Python and Bash

Build dynamic test environments on cloud platforms with Ansible and Terraform

Analyze threat actor behavior and abuse patterns.

Research, prototype, and implement abuse detection techniques.

Develop AI model serving infrastructure

Collaborate for successful deployment

Design, build, and maintain distributed backend systems

Work closely with product and engineering peers

Translate ideas into engineering solutions

Own end-to-end project delivery

Lead the implementation of new features and enhancements

Design, develop, and maintain front-end apps

Design and maintain cloud infrastructure with AWS/Azure/GCP

Automate provisioning using Terraform

Drive architectural vision for login flow and Auth0 management.

Lead major technical projects across teams.

Act as a customer's technical advocate and extend their team.

Implement Fastly products post-sales and document configurations.

Own and evolve the compute platform to support all workloads.

Hire exceptional engineers and invest in their growth.

Design and architect Accounting Platform systems

Mentor engineers and ensure quality standards

Design and develop data pipelines using Python, Spark, Databricks, SQL, and SSIS.

Implement ETL/ELT workflows with Apache Airflow and SSIS.

Define infrastructure architecture and address technical challenges.

Lead complex initiatives across multiple teams.

Analyze threat actor behavior and abuse patterns

Research, prototype, and implement abuse detection techniques

Design, build, and maintain scalable distributed backend systems

Work closely with product and engineering peers to shape product decisions

Develop state-of-the-art voice cloning techniques

Implement low latency and cost-effective text-to-speech solutions

Design and build scalable backend systems and APIs

Enable audience creation, segmentation, and activation on Twilio's data platform

Design, develop, and maintain Ruby on Rails web apps.

Translate product requirements into scalable technical solutions.

Provide technical leadership on automation-first customer problems

Bridge customer operations, AI, and platform teams for scalable solutions

Deliver DoD software using Agile methodology

Build applications with Python, FastAPI, and React

Lead database solution direction

Implement scalable database solutions

Analyze threat actor behavior and abuse patterns for detection.

Implement state-of-the-art LLM-driven techniques for abuse prevention.

Developing and maintaining AI model serving infrastructure

Implementing high availability applications on Kubernetes

Design, build, and maintain scalable distributed backend systems

Own backend services end-to-end

Analyze customer datasets for insights

Explain model performance and risk policies

Own critical infrastructure supporting engineering teams

Design, deploy, and operate Kubernetes platforms

Develop and deploy AI models efficiently

Prioritize tasks based on urgency and impact

Analyze threat actor behavior and abuse patterns.

Implement abuse detection techniques.

Act as technical advisor to enterprise customers

Design and implement modern data architectures

Design, build, and maintain scalable distributed backend systems

Own backend services end-to-end

Drive backend engineering

Lead design and implementation of new features

Evolve and maintain foundational Enterprise systems

Collaborate with cross-functional teams

Lead data science and ML initiatives

Build and lead a team for predictive modeling and experimentation

Build a cloud-native network stack for Airbnb services

Collaborate with open-source communities like CNCF and Istio

Design, implement, and maintain cloud infrastructure using IaC

Improve reliability, security, and scalability of the platform

Lead design and delivery of Java projects

Analyze and optimize engine performance