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.
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.
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.
Orchestrate production pipelines on Databricks Jobs with task dependencies and failure handling.
Manage model lifecycle in MLflow and Unity Catalog across dev, QA, and production.
Ensure operational continuity with cost monitoring, observability, and incident diagnosis.
Muttdata builds innovative data products and machine learning solutions for demand planning, forecasting, and e-commerce. As a fast-growing, remote-first startup, they value ownership, collaboration, and continuous learning.
Own the ML infrastructure end-to-end, from pipelines to production.
Build data products from internal signals like conversion and expansion.
Cross team boundaries, shipping in engineering's repos and driving cross-team work.
Clerk solves the user identity layer for developers, providing full-stack React components and hooks for authentication and user management. A globally distributed, deliberately small and senior team focused on building best-in-class developer infrastructure for AI software.
Develop, train, and optimize machine learning models using Python and common ML libraries.
Support data preprocessing, feature engineering, and CI/CD integration for scalable ML solutions.
Collaborate with data engineers and stakeholders in an Agile environment to align ML solutions with business needs.
Makpar is a professional and technical solutions provider for the Federal government, specializing in cloud engineering, data management, cybersecurity, and emerging technologies. The company's connected and engaged workforce is dedicated to delivering success for clients and the American people.
Develop and deploy machine learning models to detect web-based malware at scale.
Use production data to train and evaluate models for accurate threat detection.
Collaborate with security analysts to optimize detection and cleanup processes.
The company specializes in cybersecurity, using machine learning to detect web-based malware. It operates a remote-first culture with dedicated technical resources and a focus on collaboration and innovation.
Own end-to-end performance optimization for production ML workloads, from bottleneck identification to rollout.
Diagnose ML performance bottlenecks across model execution, frameworks, runtimes, memory, and CPU/GPU utilization.
Design and implement improvements in inference execution, runtime behavior, batching, memory management, and precision.
Reddit is a community of communities, hosting open and authentic conversations across the internet. With over 100,000 active communities and approximately 130 million daily active users, it is one of the web's largest sources of information.
Build and operate production ML systems for recommendations, ranking, and personalized action selection across Stripe's Growth Platform.
Improve contextual bandit and policy-learning approaches, including exploration, reward design, and adaptive user feedback.
Develop reliable data and feature pipelines, reusable tooling, and online experiments to drive measurable business outcomes.
Stripe is a financial infrastructure platform for businesses of all sizes, enabling payments and revenue growth. With millions of companies as customers, Stripe fosters a culture of passion, grit, and integrity while working to increase the GDP of the internet.
Identify and implement AI/ML opportunities across products, including generative AI and LLM applications.
Build, evaluate, deploy, and maintain machine learning models in production.
Collaborate with product managers, engineers, and experts to translate business challenges into scalable ML solutions.
The company applies machine learning and AI to real-world business and product challenges. It fosters a collaborative, remote-first environment centered on technical learning, innovation, and professional development.
Own, debug, and improve production ML pipelines for accuracy and efficiency.
Design LLM evals, LLM-as-a-judge systems, datasets, and benchmarks to monitor quality.
Run experiments on prompts, models, and pipeline designs to drive improvements into production.
Mimica is an AI-powered process intelligence platform that helps enterprises reclaim time by analyzing workflows and generating AI agents to automate tasks. Backed by $26M in Series B funding and trusted by Fortune 500 companies, the remote-first team spans 16+ countries and values high ownership and transparent communication.
Build and maintain automated, tested ML/data pipelines to take data science models from notebooks to production.
Optimize CI/CD, workflow orchestration, and observability to keep match data reliable at scale.
Partner with data science to maintain feature pipelines, run EDA, and apply AI tools across workflows.
PAR Technology is a leader in restaurant technology, providing software and hardware that help brands create guest connections and drive growth. Serving over 100,000 restaurants in 110+ countries, it fosters a collaborative 'Better Together' culture within its growing SaaS organization.
Own customer solutions end-to-end: rapidly prototype, iterate, and deploy solutions in live operational environments.
Build trusted relationships from IC level to executive sponsor and become the technical face of the company.
Run multiple customer engagements in parallel, setting expectations and owning outcomes.
Kinaxis is a global leader in modern supply chain orchestration, powering complex global supply chains with an AI-infused platform. We have grown to over 2000 employees worldwide with a best-in-class HQ in Ottawa and are proud winners of several Top Employer awards.
Lead the team in roadmapping and executing machine learning features and products.
Improve team pace through technical expertise and pragmatic tradeoffs.
Drive recruiting, reliability, and growth of team members.
Hightouch helps companies sync data into their SaaS systems to automate and improve operations. They are a remote-first company with hundreds of customers and a culture focused on engineering excellence.
Build and ship production AI systems for the core finance workflows.
Own evals: metrics, test datasets, and monitoring of quality, cost, and latency.
Iterate end-to-end on AI products, from data pipelines to deployment.
Sibill is an AI-powered platform that unifies invoicing, payments, treasury, and accounting for SMEs and accountants in Italy. Backed by €12M from Creandum, the company serves over 5,000 businesses and 300+ firms with a team of over 130 people.
Design, build, and maintain scalable real-time ML services for ranking and personalization.
Analyze user behavior and run A/B tests to improve product discovery and engagement.
Collaborate with engineers, data specialists, and business stakeholders to drive measurable outcomes.
The company is an AI-driven e-commerce platform that uses machine learning to power smarter search, discovery, and shopping experiences. It maintains a collaborative, remote-first culture that values ownership, inclusion, and meaningful impact.
Develop deep understanding of customer problems and map them to Cohere solutions as a trusted technical advisor.
Lead design and deployment of customer pilots, owning the technical narrative from discovery to business case.
Collaborate with Product and Engineering teams and partners to scale solutions and gather customer feedback.
Cohere is a leading security-first enterprise AI company building cutting-edge foundation AI models and products for real-world business problems. It is a global team of researchers, engineers, and designers headquartered in Toronto with offices worldwide, committed to driving AI adoption.
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.
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.