Top Tech Jobs & Startup Jobs

Build and maintain Python backend services and internal tools for AI/LLM applications. Integrate LLM APIs, design scalable REST APIs and async workflows, handle prompt management and model routing, monitor performance, debug distributed systems, automate data workflows, and collaborate to productionize AI features with emphasis on scalability, reliability, and safety.

Hands-on People Operations Generalist supporting HR, talent acquisition, onboarding, employee relations, payroll validation, compliance, workforce administration, and project launch coordination. Partners with leaders and cross-functional teams to improve processes, support employees, run recruiting activities, and contribute to employer branding and outreach in a fast-paced global environment.

Source and screen candidates globally for technical and non-technical roles, build proactive talent pipelines, conduct virtual interviews and assessments, prepare candidate packages, collaborate with recruiters and hiring managers, and maintain ATS and market intelligence to deliver qualified candidates across 115+ countries.

Source candidates globally for technical and non-technical roles, build proactive pipelines, conduct virtual screenings, evaluate and present candidate packages, partner with recruiters and hiring managers, and provide market intelligence to improve sourcing strategies and processes.

Participate in a one-time, guided ~20-minute English voice recording session from home to support AI speech research. Use your own compatible device, follow provided instructions, record in a quiet indoor environment, and complete required registration form. Approved participants receive $25 after quality review. Eligibility limited to adults residing in specified U.S. states.

Provide expert finance domain evaluation of AI-generated investment analyses: validate reasoning, identify factual or calculation errors, review valuation and financial models, create and refine prompts and benchmarks, annotate datasets, and deliver structured feedback to improve LLM performance while collaborating with project teams in a remote, project-based role.

Apply expert investment research and capital markets knowledge to evaluate AI-generated financial analyses, validate models and valuations, identify errors, create and refine prompts and benchmark datasets, and provide actionable feedback to improve LLM performance while meeting quality and turnaround expectations.

Design, build, and deploy production-grade backend services and LLM-powered applications. Implement RAG pipelines, integrate LLM providers, manage vector databases and embeddings, optimize performance, and collaborate with product and engineering teams to deliver secure, scalable AI solutions.

Use finance expertise to create realistic finance prompts, develop reference answers, and evaluate LLM outputs for accuracy, reasoning, completeness, and real-world applicability. Provide structured scoring, detailed feedback, and benchmarking to improve AI model quality. Work full-time on retainer with strict time-zone availability.

Paid remote study: complete a one-time guided English voice recording session (≈20 minutes) from your own compatible device. Participants should speak Chinese-influenced English (EN-ZH), be 18+, reside and record from an approved U.S. state, follow provided instructions, and will receive $18 for approved completion.