Lead AI/ML Engineer, Algorithms & Research

Upwork ($UPWK) is the world’s work marketplace. We serve everyone from one-person startups to large, Fortune 100 enterprises with a powerful, trust-driven platform that enables companies and talent to work together in new ways that unlock their potential. Last year, more than $3.8 billion of work was done through Upwork by skilled professionals who are gaining more control by finding work they are passionate about and innovating their careers.

The Algorithms and Research Team within the ML & AI organization is responsible for building the  foundational models that support all vertical teams, including Search & Recommendations and Upwork’s latest initiative, developing Uma, our AI assistant.

As a Lead Machine Learning Engineer/Scientist, you will play a crucial role in developing and maintaining discriminative and generative AI models. You will design, train/finetune, and evaluate information retrieval systems capable of handling both structured and unstructured databases. Leveraging historical context and diverse data, you will create innovative models to drive significant business impact.

Key Responsibilities:

• Design and develop retrieval augmentation methods for structured, unstructured and relational databases.
• Develop and utilize knowledge graphs for information retrieval. Orchestrate information retrieval using knowledge graphs in the loop.
• Investigate model explainability and work with trust and safety teams to enhance reliability and reduce hallucination in Gen-AI models.
• Collaborate cross-functionally with machine learning engineers to take models from research to production.
• Stay current with the latest advancements in Gen-AI and integrate relevant innovations into our systems.
• Mentor junior engineers, conduct code reviews, and enforce engineering best practices. Deliver high-quality solutions that improve overall efficiency.

What it takes to catch our eye:

• Proven experience in designing and developing information retrieval or RAG systems.
• Expertise in vector and graph databases.
• Expertise in Graph Neural Networks (GNNs) and related concepts
• Familiarity with knowledge graphs and ontology engineering
• Familiarity with search and recommendations in two sided marketplaces
• Passion for developing autonomous agentic systems using LLMs
• Strong publication record in top-tier conferences like NeurIPS, CVPR, ICML, ICLR, etc.

The annual base salary for this position in California and Washington ranges from $186,000 – $279,000.