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.
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.
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.
Develop and deploy full-stack ML models for financial crime detection in transaction processing and onboarding.
Own the Dynamic Risk Score (DRS) system, scoring clients daily and driving quarantine and alert decisions.
Set up monitoring and champion-challenger frameworks to ensure best models are always in production.
Finom is a European tech startup developing an all-in-one financial B2B platform integrating banking, accounting, and invoicing. With over 300 employees and a start-up culture, they prioritize innovation, swift implementation, and employee empowerment.
Manage and guide engineering teams, building end-to-end data pipelines using Fivetran, dbt, Snowflake, and Databricks.
Partner with Finance, Sales, and Operations to unify reporting models for pipeline health, ARR, churn, and LTV.
Enforce data governance and modeling standards, while serving as a trusted advisor to C-suite leaders.
JumpCloud is the AI-powered unified IT management platform that secures the modern workforce by consolidating identity, device, and access management. It is a remote-first company with teams in over 15 countries, fostering a collaborative and inclusive culture.
Develop machine learning algorithms for device identification using noisy, unlabeled data.
Design supervised, semi-supervised, and unsupervised ML approaches.
Own projects from research through deployment to real-time services.
This partner company develops a high-volume, real-time identification platform for browsers and devices. It prioritizes engineering excellence and data-driven decisions, with a globally distributed team of specialists.
Lead technical design and architecture for Medium's ML recommendation backend.
Build and scale feature store, recommender systems, and ML Ops.
Mentor engineers and drive cross-functional technical direction.
Medium is an online publishing platform that connects millions of readers with ideas and stories. The company values engineering excellence, collaboration, and a culture of mentorship and continuous improvement.
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 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.
Develop and deploy statistical and machine learning solutions for a major U.S.-based e-commerce retailer.
Collaborate with project leadership, data specialists, and engineering teams to translate business challenges into analytical models.
Drive end-to-end data science projects from data exploration and feature engineering through predictive modeling and production deployment.
The company is a technology consultancy that delivers data science and machine learning solutions to clients. It is a growing, fully remote organization that values continuous learning and professional growth.
Design and build ML infrastructure and GenAI models for voice and speech, including LLMs, RAG, and real-time audio at scale.
Partner with engineering teams to integrate AI capabilities into customer-facing products, ensuring scalable and reliable solutions.
Mentor engineers, explore emerging AI tech, and contribute to a collaborative, autonomous, and innovative culture.
Jobgether is an AI-powered job matching platform that connects candidates with hiring companies. The company focuses on using technology to streamline recruitment processes and ensure fair candidate evaluation.
Refactor and upgrade existing ML models into standardized, production-ready modular contracts.
Engineer resilient ML workflows with DAG-based orchestration tools like Argo Workflows and Airflow.
Build infrastructure for shadow testing, A/B testing, and structured feedback pipelines for safe deployment.
Smart Working connects skilled professionals with outstanding global teams and products for full-time, long-term roles. It is a remote-first company known as one of the highest-rated workplaces on Glassdoor, fostering a genuine community that values growth and well-being.
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.
Improve existing machine learning ranking models using core coding skills and ML knowledge.
Take end-to-end ownership of machine learning systems from data pipelines to production integration.
Identify new opportunities to apply machine learning to different parts of the Quora product.
Quora is a global knowledge sharing platform and Poe, a cloud workspace for AI agents. It is a privately held, remote-first company with a culture rooted in transparency, idea-sharing, and experimentation.
Lead the design, implementation, deployment, and operation of complex platform capabilities supporting the machine-learning lifecycle.
Build reusable platform components, standards, and automation while improving reliability, scalability, and observability across ML systems.
Partner with Data Science, Product, Risk, Fraud, and Engineering teams to translate ambiguous business needs into practical technical solutions.
Oportun is a mission-driven financial services company that helps members build a better financial future through intelligent borrowing, savings, and budgeting. The company has provided over $22.7 billion in responsible credit and its culture emphasizes speed, high standards, and the thoughtful use of AI.