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Master's thesis applying sequence-to-sequence deep learning to multivariate time series data from motorcycle test rides to predict riding states for future assistance systems, using Python, PyTorch, and XAI methods.
Builds and deploys AI-driven payment systems (LLM-powered workflows, fraud detection, personalized checkout) at scale for Airbnb’s global transactions, optimizing payouts/collections while ensuring low latency and security.
Build and scale large-scale ML infrastructure for Reddit’s recommendation systems, designing models, training pipelines, and low-latency serving to improve personalization across the platform.
Data Scientist focused on Computer Vision & AI developing, training, and optimizing ML/DL models for image-based road infrastructure analysis using Python, PyTorch, and related CV libraries at an AI-driven SaaS startup.
Builds and deploys AI models for computer-vision pipelines that help cities manage road infrastructure, using Python, PyTorch, and Kubernetes.
The AI Embedded Engineer IV integrates AI models onto autonomous vehicle hardware, managing the deployment, optimization, and real-time performance of robotics software. This role balances software development in C++ and Python with hands-on hardware tasks like sensor integration, wiring, and field testing.
This role involves driving applied research and product-oriented data science for an Agentic AI platform, focusing on LLM fine-tuning, evaluation, and knowledge graph development. The position requires deep technical expertise in machine learning and production-scale AI deployments to deliver robust agentic solutions.
The Applied AI Engineer will build and deploy end-to-end AI features by integrating machine learning models into production systems. The role involves optimizing model performance, designing agent workflows, and ensuring reliability using technologies like Python, PyTorch, JAX, and LLMs.
Build and improve production ML components across data pipelines, training, evaluation, and inference using Python, PyTorch/JAX on GPUs.
Build end-to-end AI-native product features using Next.js, Python, and Node.js, designing agent workflows that integrate LLMs, memory, and external tools into reliable, production-grade systems.
Backend Engineer building and operating the AI inference and orchestration layer that connects LLMs to end users, focusing on latency, reliability, and production operations using Python, Node.js, Kubernetes, and Docker.
The Assistant Manager (Data Science) will develop predictive models, AI/ML solutions, and automation tools to improve patient care and hospital operations. The role involves managing complex healthcare datasets and leading digital strategic initiatives using Python, R, SQL, and various AI frameworks.
Design and train reinforcement learning policies for robot movement and control, then deploy them on physical hardware while iterating based on real-world performance.
Lead a team building scalable, high-performance admin interfaces and services for Adobe’s enterprise platforms using React, Node.js, and cloud infrastructure, while driving engineering standards and mentoring engineers.
The Sr Fleet Analyst will develop analytics and KPIs to drive continuous improvement and strategic direction of the fleet, creating dashboards and reports. They'll use tools like SQL, Python, Tableau, and AI technologies to monitor fleet performance and provide insights to leadership.
Build and deploy agentic and generative AI solutions using Python, LLMs, and ML models to solve real business problems in a cross-functional team.
The Applied AI/ML Vice President will design, develop, and productionize AI/ML solutions for Asset & Wealth Management, utilizing Python, NLP, and machine learning frameworks. The role involves collaborating with stakeholders to solve complex business problems and coaching team members.
The Lead AI Engineer will design and deploy production-grade computer vision and speech processing pipelines for Digital Green's multilingual agricultural advisory platform, FarmerChat. This role involves building optimized inference systems, defining evaluation frameworks, and mentoring junior engineers to support smallholder farmers globally.
This role is a hands-on product leadership position responsible for the AI/ML roadmap of the Operator Suite, a B2B platform for venue parking management. The candidate will define product strategy while acting as an individual contributor to prototype and evaluate predictive models, dynamic pricing, and LLM-based applications.
Principal-level ML architect at Adobe responsible for end-to-end technical coherence across large-scale distributed training systems, inference infrastructure, model architecture, and data pipelines for next-generation video and image foundation models (GenRender6/Gen6.5, GenEdit1).
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