Point your AI agent at freehire and let it find you a job. A CLI and an MCP server over the whole job API — no browser.
Designs and builds scalable AWS-based ML/data infrastructure for enterprise AI solutions, focusing on MLOps, feature engineering, and governance to enable production-ready AI at scale.
What is the opportunity? Global Functions Technology (GFT) is part of RBC’s Technology and Operations division. GFT’s impact is far-reaching as we collaborate with partners from across the company to deliver innovative…
As a Machine Learning Research Engineer at RBC Borealis, you’ll build ML-based software solutions, collaborate with stakeholders, prototype algorithms, and integrate them into products using Python 3.x, PyTorch, JAX, or Tensorflow, focusing on generative AI, NLP, and time series analysis.
AI/NLP Engineer at BoomerangFX will design and deploy NLP pipelines, build RAG systems, fine-tune LLMs, and develop HIPAA/PIPEDA-compliant AI features integrated into .NET8/ReactJS platform on Azure for healthcare practice management.
Summary The Senior Machine Learning Engineer, AI Evaluation builds and operates the measurement and engineering infrastructure supporting the organization's Applied AI Research (AAIR) function, a continuous…
Higgsfield AI is seeking a Machine Learning Engineer to build and optimize advertising systems that integrate generative AI for creative generation and performance targeting. The role involves developing production-scale ML models for ranking, recommendation, and creative optimization while working in a hybrid capacity in San Francisco.
The Senior Machine Learning Scientist will design, build, and deploy production-grade AI and GenAI services for wholesale banking use cases. The role focuses on MLOps/LLMOps, infrastructure, and collaborating with cross-functional teams to ensure scalable and secure model delivery.
Machine Learning Engineer at Deeter Analytics building deep-learning models on market data, working end-to-end from raw data to production models using Python, PyTorch, and GPU infrastructure in a fully remote role.
The Senior Machine Learning Engineer will build, improve, and operate production-grade multimodal AI systems for the Pegasus video-language model. The role involves working across the full ML stack, including inference, deployment, and evaluation, to turn video data into structured, actionable insights.
The AI/ML Integration Specialist will lead the integration of secure AI solutions like Microsoft Copilot within Army environments to enhance productivity, automation, and decision support. The role focuses on ensuring AI capabilities are compliant, authorized, and mission-aligned.
Designs and builds scalable cloud-native AI/ML and GenAI infrastructure for Toyota Financial Services, focusing on MLOps/LLMOps, GPU-accelerated compute, and secure model deployment at enterprise scale.
Lead the design, development, and deployment of AI/ML-powered applications and microservices on Kubernetes, using MLOps/AIOps tools and cloud platforms to deliver scalable, production-grade solutions.
Build and train 4D world models that reconstruct dynamic scenes from multi-camera video and sensor data, turning real-world captures into high-fidelity simulation environments for autonomous vehicles and Physical AI.
Designs and deploys AI/ML and generative AI solutions (LLMs, RAG, vector databases) for enterprise applications, focusing on document intelligence, knowledge management, and automation to improve operational efficiency in climate and energy solutions.
Builds and deploys AI/ML and GenAI systems for healthcare, focusing on scalable data pipelines, model serving, and advanced GenAI patterns to solve health-related problems across Asia.
Optimizes large-scale ML workloads on GPU/CPU infrastructure for G-Research’s quantitative finance platform, profiling, benchmarking, and tuning distributed jobs to improve efficiency and scalability for researchers.
Build and deploy ML models and generative AI features to automate and enhance Zendesk’s customer-service platform, collaborating with scientists, engineers, and product teams.
Designs and maintains Unity’s offline ML platform for analytics, experimentation, and AI-driven decision-making, focusing on scalable data pipelines, distributed model training, and infrastructure reliability.
Student engineer builds and validates CI/CD pipelines, test suites, and observability tooling for Amazon’s ML accelerator hardware and inference software stacks.
NVIDIA is seeking interns for their Deep Learning Computer Architecture teams to work on projects involving GPU/CPU architecture, performance modeling, and parallel programming. Interns will utilize technologies such as C++, CUDA, and deep learning frameworks to solve complex computing challenges.
We couldn't check your fit for this role — add a CV to your profile to see it next time.
