Top Remote Jobs

Bring companies to Refer by identifying hiring organizations, pitching the AI career agent, and converting them into signed customers. This commission-only role offers complete schedule and location flexibility, with earnings based on each company acquired and no base salary or commission cap.

Provides bilingual Portuguese customer support by answering inquiries, explaining products and services, troubleshooting issues, resolving complaints, and documenting customer interactions. Maintains current product knowledge and delivers professional service remotely. Candidates must be U.S. residents, at least 18, have a high school diploma or equivalent, pass background and drug screenings, and meet specified home-office technology requirements.

Lead business development, capture, and proposal efforts for U.S. Department of the Navy initiatives. Develop growth strategies, identify opportunities across Navy system commands, manage proposal lifecycles, build stakeholder relationships, monitor competitors, and ensure regulatory compliance. The role also involves mentoring teams, influencing cross-functional stakeholders, presenting proposals, and managing multiple priorities in a fast-paced defense engineering environment.

Analyze and exploit infrared and OPIR sensor data, including SBIRS systems; develop sensor models and advanced processing algorithms in Python and MATLAB; investigate infrared phenomenology; design tests and experiments; troubleshoot data workflows and software logic; and support CONOPS, technical documentation, and technology transition efforts with government, industry, and research partners.

Lead cross-functional agency projects from planning through completion, managing schedules, budgets, risks, communications, client expectations, vendors, approvals, and project quality. The role coordinates integrated teams, maintains project management systems such as Kantata or Workfront, resolves issues, motivates contributors, and ensures projects are delivered on time, within budget, and to high standards.

Lead the design and delivery of complex automated material handling systems, including conveyors, sortation, pallet handling, AS/RS, robotics, and integrated technologies. Evaluate customer requirements, develop system layouts, drawings, technical proposals, cost estimates, documentation, and bills of material. Support projects from concept through execution and integration, coordinate with customers, suppliers, and subcontractors, conduct site visits, review technical work, and mentor engineering team members.

Lead enterprise customer onboarding and software implementations, translating business requirements into system designs and guiding launches through project milestones. Train customers and internal teams, manage VP and C-suite stakeholders, resolve implementation challenges, and collaborate across Support, Integration, Product, and Sales. Drive continuous improvement, change management, and customer success while working with configurable QMS and frontline-worker software in regulated industries.

Drive new client acquisition and revenue growth in the U.S. crypto payments market. Manage the full B2B sales cycle from prospecting through closing, maintain CRM pipeline activity, meet sales targets, develop partner relationships, analyze market trends, improve attach rates, and provide weekly revenue forecasts. The role requires strong Web3 knowledge, established crypto industry connections, proven market-share growth, and over five years of relevant sales experience.

Supports the Data Science and Machine Learning team by analyzing large-scale datasets, identifying anomalies and root causes, developing data validation and normalization methods, and improving the accuracy of derived data products. The intern will evaluate models, translate ambiguous problems into statistical formulations, debug messy data, test hypotheses, and implement maintainable analytical solutions using Python, SQL, and distributed data platforms.

Design and maintain scalable services, APIs, distributed systems, and data pipelines for AI training data infrastructure. Own systems through design, implementation, testing, deployment, and monitoring. Lead architectural decisions, improve reliability and scalability, mentor engineers, and collaborate with AI/ML, product, and data operations teams. Contribute to CI/CD, containerization, DevOps, and cloud deployment practices.