Upwork

Full-stack Engineer

• Collect high-quality training data and curate datasets for supervised, unsupervised, and reinforcement learning use cases
• Build scalable featurization and preprocessing pipelines to transform raw data into structured inputs for AI/ML model development
• Partner with ML engineers and researchers to define data requirements and production workflows for LLM-based agents and autonomous AI systems
• Lead development of infrastructure enabling experimentation, evaluation, and deployment of machine learning models in production
• Support orchestration and real-time inference pipelines using Python and cloud-native tools, ensuring low-latency and high availability
• Mentor engineers and foster a high-performance, collaborative engineering culture
• Drive cross-functional alignment with product, infrastructure, and research stakeholders on progress, goals, and architecture

Lead Software Engineer, AI Data Systems

Backend Engineer

• Design, build, and maintain APIs for the AI/ML Services Interface with reliability, scalability, and performance as core priorities
• Partner with frontend and backend engineers to define API contracts and deliver seamless integrations
• Implement and strengthen API security, authentication, and authorization mechanisms
• Conduct code reviews, provide constructive feedback, and ensure adherence to engineering best practices
• Monitor, troubleshoot, and continuously improve API performance and developer experience
• Stay current with API development trends, frameworks, and tools, sharing insights with the team
• Take ownership of projects, contribute to shaping API standards, and work on complex, high-visibility initiatives that impact millions of users

Senior API Engineer

Director

• Lead end-to-end M&A and investments execution including sourcing, valuation, due diligence, negotiations, and post-merger integration
• Build and oversee detailed evaluation exercises, valuation models, ROI frameworks, and scenario analyses to evaluate deal economics
• Prepare investment / M&A memos and presentations for leadership and the Board of Directors
• Drive post-deal integration with cross-functional leaders, set KPIs and milestones to measure integration success
• Partner with Corporate Strategy to advance market, competitive, and ecosystem intelligence
• Provide strategic direction, mentorship, and performance management to the Corporate Development team
• Cultivate relationships with bankers, VCs, advisors, and entrepreneurs
• Report to the VP of Strategy, Corporate Development & Partnerships with high executive visibility

Senior Director, Corporate Development

Product Manager

• Provide coverage through the end of the year on high-visibility Ads & Connects initiatives.
• Drive strategy and execution for Boosted Profiles (talent-side) and Featured Job Post (client-side).
• Partner with senior leaders to shape marketplace design, launch experiments, and deliver measurable revenue and growth results.
• Work cross-functionally with analytics, design, economics, pricing, FP&A, and marketing.
• Define, prioritize, and deliver roadmap enhancements with cross-functional partners.
• Design, run, and evaluate experiments; translate insights into strategic product decisions.
• Track and interpret key metrics to ensure revenue-impacting initiatives are aligned and on schedule.
• Simplify complex product challenges using first-principles thinking, data analysis, and informed intuition.
• Ensure cross-team alignment and timely delivery of milestones, keeping stakeholders engaged and accountable.

Senior Product Manager, Ads & Connects

Human Resources

• Serve as a trusted advisor to employees and leaders across the business, advancing a culture of engagement and inclusion while supporting day-to-day HR needs and strategic initiatives.
• Provide coaching and guidance on employee relations, conflict resolution, and workplace matters, ensuring fair and consistent outcomes.
• Act as a trusted partner for employees and managers, balancing advocacy for people with business needs.
• Lead and continuously improve HR programs, with a strong focus on performance management, offboarding, and organizational planning and design.
• Facilitate coaching conversations with managers and employees to strengthen leadership capability, improve team performance, and build a culture of accountability and development.
• Collaborate on organizational planning, change management, and employee engagement initiatives that improve workplace culture.
• Leverage HR data and analytics to identify trends, inform decisions, and recommend actions that improve employee experience and business results.
• Partner with cross-functional HR colleagues to ensure consistent application of policies, compliance, and best practices across the organization.

Senior HR Generalist

• Design and implement systems to collect and curate high-quality training datasets for supervised, unsupervised, and reinforcement learning use cases
• Build scalable featurization and preprocessing pipelines to transform raw data into structured inputs for AI/ML model development
• Partner with ML engineers and researchers to define data requirements and production workflows that support LLM-based agents and autonomous AI systems
• Lead the development of infrastructure that enables experimentation, evaluation, and deployment of machine learning models in production environments
• Support orchestration and real-time inference pipelines using Python and modern cloud-native tools, ensuring low-latency and high availability
• Mentor engineers and foster a high-performance, collaborative engineering culture grounded in technical excellence and curiosity
• Drive cross-functional alignment with product, infrastructure, and research stakeholders, ensuring clarity on progress, goals, and architecture
• Build scalable, performant systems to support model training and inference at scale

Lead Software Engineer

Infrastructure Engineer

• Lifecycle Automation: Design and deliver automation to package, test, deploy, and operate infrastructure globally. Build systems that enforce lifecycle patterns and eliminate manual workflows at scale.
• Cloud Infrastructure Engineering: Deploy and manage infrastructure across AWS, Azure, GCP, or OCI. Architect for scale, fault tolerance, and operational simplicity with cost, performance, and security as core design constraints.
• Infrastructure-as-Code and CI/CD: Deliver secure, reusable infrastructure using Terraform, Packer, or Chef. Architect CI/CD pipelines using ArgoCD, Tekton, or Jenkins with GitOps workflows that support rapid, safe delivery.
• Containerization and Service Deployment: Design and deploy containerized applications using Docker, Kubernetes, and Rancher. Own service lifecycle patterns including ECS, EKS, and EC2-based deployments.
• Security and Vulnerability Lifecycle Management: Embed secure configuration, patching, and vulnerability remediation into platform automation. Use infrastructure-as-code and policy-as-code to enforce drift control and reduce risk at scale.
• AI/ML-Powered Infrastructure Ops: Use AI models and agent-based systems to automate support, detect anomalies, triage alerts, and reduce human effort. Shift operational ownership from engineers to intelligent systems by default.
• Observability and Signal-Driven Automation: Build and operate system observability with tools like ELK and Prometheus. Integrate telemetry with signal-aware automation to trigger remediation, suppression, or escalation based on policy.
• Tooling and Platform Engineering: Build tools and frameworks that improve developer experience, infrastructure safety, and delivery velocity. Write systems that interact with APIs, version control, and internal platforms.
• Documentation and Engineering Hygiene: Maintain high-quality documentation for all infrastructure systems and workflows. Replace tribal knowledge with versioned, discoverable, and actionable references.
• Cross-Team Technical Leadership: Partner with application engineers, SREs, platform teams, and security to deliver shared tooling, drive adoption of standards, and scale infrastructure patterns across teams.

Senior Infrastructure Engineer

Solutions Engineer

Upwork ($UPWK) is the world’s work marketplace.
This is an engagement through Upwork’s Hybrid Workforce Solutions (HWS) Team; HWS is a global group of professionals that support Upwork’s business.
Design and develop AI-powered tools and applications to improve productivity across Upwork.
Build and maintain scalable, secure, and reliable server-side services and APIs.
Integrate AI technologies, LLMs, MCP, RAG, and other advanced architectures into workflows and business systems.
Develop and maintain integrations with existing SaaS solutions via their APIs, leveraging integration platforms or custom connectors.
Collaborate with stakeholders to identify pain points, map business processes, and design AI-driven solutions.
Develop end-user applications that make AI capabilities intuitive and accessible to non-technical audiences.
Create and manage ETL processes, pipelines, and data models for AI and analytics workloads.
Prototype and experiment with emerging AI tools to evaluate potential business impact.
Apply modern authentication and security practices, including OAuth 2.0, OpenID Connect, and SAML.
Ensure operational excellence in the deployment, monitoring, and scaling of AI solutions.

AI Productivity Solutions Engineer

Data Engineer

• As a Lead AI Data Engineer on our Data Platform & Services (DPS) team, you’ll combine advanced data engineering expertise with cutting-edge AI practices to deliver production-grade systems that transform how Upwork uses data. You’ll design and deploy agentic frameworks, natural language querying (NLQ) solutions, and LLM evaluation strategies that make insights accessible at scale. This is a chance to deliver visible impact—accelerating decision-making, enabling self-service analytics, and empowering stakeholders across the company.
• Responsibilities:
• Design and implement scalable agentic frameworks that coordinate multiple AI agents to deliver accurate and reliable outcomes.
• Build and optimize natural language query systems that provide intuitive, compliant, and self-service access to enterprise data.
• Develop and maintain frameworks for evaluating prompts and LLMs, driving measurable improvements in accuracy, resilience, and scalability.
• Partner with data engineering peers to integrate AI orchestration with existing pipelines using Python, SQL, and Snowflake.
• Contribute to AI-powered summarization and explanation tools that enhance reporting, insights, and executive decision-making.
• Collaborate with product, analytics, and business teams to ensure AI solutions align with measurable business goals.
• What it takes to catch our eye:
• Proven success delivering AI-powered data systems in production, including hands-on experience with LLMs and prompt engineering.
• Strong foundation in modern data engineering with expertise in Python, SQL, and platforms such as Snowflake.
• Ability to design agentic orchestration frameworks that scale across diverse business scenarios.
• Collaborative problem-solver with excellent communication skills, able to align stakeholders and create clarity across teams.
• Growth mindset—eager to learn, iterate, and deliver measurable outcomes through applied AI.

Lead Data Engineer

User Researcher

• Drive evidence-based decision-making through quantitative research that uncovers deep insights into user behavior, needs, and outcomes
• Partner across Product, Data Science, and Design to ensure decisions are rooted in statistically sound, customer-centric insights
• Design and lead robust quantitative studies (surveys, log data analysis, segmentation, conjoint)
• Integrate quantitative and qualitative data into compelling narratives to guide cross-functional decision-making
• Build and scale research frameworks such as user satisfaction metrics, trust indicators, and skill validation models
• Collaborate to refine hypotheses, align on KPIs, and translate research into measurable outcomes
• Champion research rigor and ethics, ensuring reproducibility, data quality, and responsible handling of user data
• Provide mentorship on quantitative methods to raise the analytical bar of the Research & Insights team
• Contribute to Upwork’s mission to create economic opportunities for professionals worldwide and support a remote-first workforce

Lead User Researcher – Product Insights

Data Scientist

• Upwork is the world’s human and AI-powered work marketplace connecting businesses with independent talent globally
• Data Science sits within centralized Finance and drives profitable growth and marketplace optimization
• As a Senior Data Scientist, design models that measure and predict customer behavior, lifetime value, and marketplace health
• Tackle complex problems inherent to a global double-sided marketplace and deliver insights to drive product strategy
• Partner with Product, Marketing, and Trust & Safety to surface actionable insights and shape high-impact initiatives
• Own data workflows end-to-end: cleaning, transforming, feature engineering, and schema design using Python, SQL, pandas, and Snowflake
• Build and scale models and analyses using platforms such as AWS SageMaker, Hex, or Snowflake, ensuring repeatable and reliable workflows
• Communicate findings to technical and non-technical audiences to influence strategic decision-making

Senior Data Scientist

• Lead the full product lifecycle for AI and agent-based solutions, from discovery and definition to launch, iteration, and scaling.
• Define and maintain a product roadmap that balances near-term deliverables with long-term innovation.
• Collaborate with engineering and design to scope, build, and deliver features that meet user needs and business goals.
• Partner with research and analytics to uncover opportunities, validate concepts, and guide decision-making using data-driven insights.
• Engage with customers to gather feedback, identify pain points, and translate insights into actionable improvements.
• Stay current on advancements in AI, machine learning, and agentic systems to assess emerging capabilities.
• Align and coordinate cross-functional teams, ensuring timely delivery against success metrics.