Train, evaluate, and deploy spam-detection models, building and maintaining training corpora and analyzing precision and recall.
Develop production components of a new email-filtering engine in Go, including inference services and streaming message parsing.
Investigate customer-reported incidents and improve detection quality through rules, datasets, or model retraining.
This partner company develops advanced machine learning technology to protect email infrastructure against spam, phishing, and other evolving cyber threats. It operates a production-scale security solution filtering email across approximately 5,000 hosting servers and values remote-first, flexible working with a focus on engineering excellence.
Own end-to-end ML systems from data and training to evaluation, inference, and deployment.
Build and evolve training, fine-tuning, and inference infrastructure for large models.
Partner with research and application engineering to turn model capabilities into product improvements.
Next Step Systems is an IT recruiting and staffing agency that connects companies with machine learning and technology talent. They specialize in placing candidates in remote and on-site roles across the United States and emphasize a fast-paced, results-oriented culture.
Lead the end-to-end machine learning lifecycle, from data preparation and model training to evaluation, inference, and deployment.
Build and optimize scalable training, fine-tuning, and inference pipelines for large-scale models on GPU infrastructure.
Establish production best practices for model quality, reliability, safety, and measurable performance improvements.
This company builds production-grade machine learning systems and large-scale GPU-powered inference pipelines. It is a fully remote team that values technical rigor, collaboration, and hands-on engineering.
Build LLM-powered agents and production ML systems to automate security analysis.
Collaborate with threat-research and data engineering to turn risk identification into scalable solutions.
Own deployment, monitoring, and quality of solutions in CI/CD frameworks.
Zscaler accelerates digital transformation with its Zero Trust Exchange platform, protecting customers from cyberattacks and data loss. The company is the world's largest in-line cloud security platform, distributed across 160+ exchanges, with an AI-native culture focused on ownership, collaboration, and trust.
Design, deploy, and optimize large-scale ML systems for retrieval, ranking, and LLM-powered features.
Lead ML projects from concept to production, improving answer relevance and user experience.
Collaborate with Product, Data Science, and Engineering teams to shape technical direction.
The hiring partner is a technology company focused on building advanced AI systems that help users discover relevant answers from large collections of online conversations. It values innovation, collaboration, and responsible AI development, offering a remote work environment within the United States.
Build the component layer around our layout synthesis engine, including API contracts, services, and evaluation gates.
Turn model retraining into a one-command job with built-in benchmarks and readable results for the whole team.
Own latency and cost budgets for learned capabilities and partner with infrastructure engineers on MLOps and deployment.
Higharc is a VC-backed startup that is changing how new homes are designed and built using spatial AI and generative floor plan technology. The company is fully remote, has raised over $175M, and values flexibility, collaboration, and asynchronous deep work.
Own the full ML lifecycle for Misdirected Email detection, from data wrangling to deployment and monitoring.
Run rigorous experiments and A/B tests, set thresholds, and conduct error analysis to prevent regressions.
Partner with product and engineering stakeholders to align deliverables and ensure successful GA launches.
Abnormal protects the humans behind the world's most critical organizations from AI-powered cybercrime. 5,000 enterprises trust our behavioral AI platform.
Collaborate with Data Science teams to deploy and maintain machine learning models in production environments.
Build robust data processing pipelines and implement MLOps and LLMOps best practices for scalable AI solutions.
Work with cloud technologies, big data platforms, and machine learning frameworks to deliver innovative technical solutions.
The company specializes in data and technology services, helping transform machine learning solutions into production-ready systems. It is an established international organization with a collaborative, inclusive culture and a strong emphasis on continuous learning and career growth.
Build and maintain production-grade machine learning infrastructure for AI governance and trust, including model serving, evaluation, and monitoring.
Develop low-latency inference systems, model registries, and evaluation pipelines for reliable model lifecycle management.
Design and implement red-team testing, drift monitoring, and continuous retraining loops using telemetry and audit data.
The company builds AI governance and trust infrastructure, including production ML systems for AI agents. It offers a remote-first, international engineering organization with a focus on security and reliability.
Build new functionality within a fast-moving product, taking ambiguous ideas from design to rigorous experimentation within weeks.
Conduct deep-dive research into state-of-the-art LLM orchestration, retrieval strategies, and data-driven personalization.
Build production-grade ML systems at Twilio scale, leveraging the latest AI development stacks to focus on core differentiation.
Twilio is a cloud communications platform that enables businesses to create personalized customer experiences through APIs and AI-driven solutions. The company is remote-first, serving hundreds of thousands of businesses, and fosters a culture of connection, inclusion, and innovation.