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.
The Software Engineer will build reinforcement learning environments to test AI models and optimize software performance. The role involves refactoring code, debugging complex issues, and implementing new features using languages like Python, Java, Rust, or TypeScript.
The Senior Software Engineer will build reinforcement learning environments to test AI models and optimize software performance. The role involves refactoring codebases, debugging complex issues, and implementing new features using languages like Python, Java, Rust, or TypeScript.
Design, develop, and deploy NLP/LLM solutions for a geospatial startup, translating research into production-ready systems. Core tech: Python, PyTorch/TensorFlow/Hugging Face, LangChain/Haystack, Docker/Kubernetes, and cloud platforms.
The Machine Learning Engineer will build data pipelines and MLOps infrastructure to support the deployment and maintenance of AI models for an insurance group. The role involves collaborating with data scientists to transition experimental models into production-ready solutions using cloud technologies.
Build Reinforcement Learning environments to test AI models' problem-solving skills, while handling complex software engineering tasks like feature development, bug fixing, refactoring, and performance optimization using Python3, Java, Rust, or TypeScript.
ML Engineer at ADASTEC training, evaluating, and deploying perception models (2D/3D object detection, LiDAR, camera-radar fusion) for SAE Level-4 autonomous driving. Core tech: PyTorch, ONNX, TensorRT, Docker GPU training.
The Senior Backend Engineer will design and develop scalable backend services, APIs, and data pipelines to support AI/ML and healthcare analytics. The role focuses on cloud infrastructure, CI/CD, and maintaining secure, observable production systems.
The Junior ML Engineer role at Zaymigo involves working on machine learning tasks within a fintech environment.
The AI/ML Platform Architect will lead the design and implementation of an AI/ML platform for a Unified Security Posture Management system. This role involves driving innovation in machine learning and automation to support product and engineering teams.
The Lead Machine Learning Engineer will design and maintain scalable ML systems while setting technical direction and mentoring engineering teams. This role involves building shared ML resources, managing project roadmaps, and providing technical coaching to customers.
As a Senior Machine Learning Engineer at Faculty, you will design and deploy production-grade ML software and scalable infrastructure while advising customers on technical strategy and mentoring junior team members.
The Solutions Engineer will work directly with customers to implement production-ready AI and software solutions using LLMs, MLOps, and cloud infrastructure. This role bridges technical expertise and customer success to drive product adoption and roadmap development.
The Process Control System Engineer will optimize semiconductor wafer manufacturing by developing AI/ML models, implementing DevOps practices, and building data-driven dashboards using Python and SQL.
The AI/ML DevOps Engineer will design and operate AI/ML models and LLM-based agent applications for pharmacy and benefits platforms. The role focuses on building scalable cloud infrastructure, managing conversation states, and integrating LLMs with enterprise systems.
The DevOps Engineer (AI/ML) will design, deploy, and maintain LLM-based agent applications and cloud infrastructure for healthcare pharmacy systems. The role focuses on building scalable AI platforms, optimizing agent workflows, and ensuring reliable deployments using Python and cloud-native technologies.
Build deployment systems, CI/CD pipelines, monitoring dashboards, and automation frameworks for AWS ML's Fleet Lifecycle & Operational Workflows (FLOW) sub-team.
This co-op researcher role involves collaborating with teams to design, implement, and benchmark state-of-the-art computer vision and machine learning algorithms.
The Machine Learning Engineer will design, build, and deploy machine learning solutions for production environments while collaborating with research and engineering teams. The role involves running experiments on large datasets and maintaining customer-facing software products.
The AI Solution Architect will develop technical conformity criteria, testing methods, and benchmarks for AI systems to ensure safety and trustworthiness in compliance with EU regulations. The role involves working in an interdisciplinary team to validate research results and support certification processes for high-risk AI applications.
About Build AI Build AI is the data hyperscaler for Physical AI. We're vertically integrated across hardware, manufacturing, logistics, collection, and model training to scale the physical labor dataset orders of…
We couldn't check your fit for this role — add a CV to your profile to see it next time.
