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AI Engineer
An AI Engineer at Tractian develops and optimizes large language model (LLM) applications and backend systems, collaborating with cross-functional teams to ensure project success and efficient deployment.
Campus AI Research Engineer - Deep Learning (Intern)
Research intern applies deep learning to financial markets, building and optimizing ML models in Python/C++/CUDA and deploying them into low-latency trading systems.
Machine Learning Engineer
Design state-of-the-art ML models and large-scale systems for Stripe Capital’s underwriting and portfolio management, using PyTorch and TensorFlow, while building scalable pipelines and collaborating with product partners.
Treasury Finance AI and Quantitative Analytics, Americas
Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow…
Machine Learning Engineer, Capital Underwriting
Designs, builds, and deploys ML models to underwrite financing offers for Stripe Capital, using PyTorch/TensorFlow and collaborating with cross-functional teams.
Campus AI Research Engineer (Intern)
Research intern builds and optimizes AI/ML systems for quantitative finance, working with PyTorch/JAX and CUDA on HPC clusters to push low-latency trading models from concept to production.
Staff Data Scientist – Simulation Motion AI
Designs scalable simulation systems to train and evaluate AI-driven robotic motion policies for medical devices, collaborating with engineering, product, and clinical teams to generate synthetic data, test algorithms, and ensure safety-critical performance.
Senior Software Engineer – Simulation & ML Platform
Builds software platforms for robotic motion AI simulation and ML, translating research requirements into scalable systems for synthetic data generation, experiment pipelines, and GPU-enabled environments.
Google AI/ML Data Scientist
Works on the Border Wait Time project, preparing traffic congestion datasets, developing ML models to predict traffic volumes, and deploying solutions with Google Vertex AI. Core technologies include Python, TensorFlow/PyTorch/scikit-learn, and Google Cloud Platform (Vertex AI, BigQuery, Cloud Storage).
Sr. Recruiter
This is a remote position. At Everyday People Inc. , we don’t do mass offshore recruiting. We build elite recruiting teams who partner directly with clients shaping the future. Including everything from autonomous…
AI/ML Engineer – Generative AI
Build and optimize cutting-edge generative AI models for image generation and multimodal applications using AMD’s GPUs, collaborating with researchers and engineers to push visual computing boundaries.
Specialised AI Engineer
Senior/Staff AI Engineer at Nscale in London building and optimizing distributed GenAI systems for training, post-training, evaluation, and high-throughput inference using Python, PyTorch, and GPU acceleration.
Data Scientist
Build meaningful data products and apply Machine Learning using Python, SQL, and AWS. The role involves data modeling and communicating insights to clients.
Manager Machine Learning Platform - Bees Data
Lead a team to build and scale the ML platform for BEES, AB InBev’s B2B digital commerce platform, using cloud-native tools and MLOps practices to enable reliable, production-grade AI systems.
Mid Level Machine Learning Engineer
Builds and maintains machine learning infrastructure for AB InBev’s B2B platform BEES, including training pipelines, inference services, and monitoring, using Python, PySpark, Kubernetes, and Azure cloud.
Senior Machine Learning Engineer
Senior Machine Learning Engineer at AB InBev Growth Group in Campinas, Brazil, building and scaling ML pipelines for the BEES B2B platform using Python, PySpark, Kubernetes, and Azure Cloud.
Senior Machine Learning Engineer
Build and scale ML systems for BEES, AB InBev’s B2B commerce platform, owning end-to-end pipelines from data to production inference.
Mid Level Machine Learning Engineer
Build and maintain ML platform components for a B2B e-commerce SaaS, including training pipelines, inference services, and observability, using Python, PySpark, Kubernetes, and Azure.