Senior Applied Machine Learning Engineer – Search & Recommendations

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October 7

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Upwork

WebsiteLinkedInAll Job Openings

B2B • Marketplace

Upwork is a leading online platform that connects freelancers with businesses, offering a wide range of professional services such as design, writing, programming, and more. It facilitates collaboration between independent professionals and clients through job postings, project catalogs, and consultations. Upwork aims to enable freelancers to find work and clients to find the best talent, providing tools to hire, manage, and pay remote talent worldwide.

501 - 1000 employees

Founded 2015

🤝 B2B

🏪 Marketplace

💰 Funding Round on 2017-01

📋 Description

• Analyze millions of structured and unstructured data to identify patterns and insights in user behavior and build meaningful features to improve model performance • Design and implement efficient and reusable features, models and systems for different machine learning applications (classical & deep learned models) in low latency fashion • Contribute to the performance and continued optimization of our recommendation systems: build machine learning models to improve understanding of user preferences, user intent and context to deliver accurate, relevant and personalized recommendations • collaborate with the business, analytics, and engineering counterparts to share the discovered data stories with stats, charts, and formal presentations, and finally propose recommendations to maximize the business impact. • Build and fine‑tune large language models (LLMs), transformers, agents, and/or hybrid systems to improve relevance, semantic understanding, and user experience.

🎯 Requirements

• Masters/PhD in Computer Science, Machine Learning, NLP, Mathematics, or a related quantitative field (or equivalent research experience). • 3+ years of relevant industry experience building large scale ML systems • Prior experience with large language models, retrieval augmented generation (RAG), or agentic AI. • Strong experience with Python, SQL PyTorch and/or TensorFlow • Clear track record of publications in peer‑reviewed conferences or journals (e.g. ACL, EMNLP, NeurIPS, ICML, ICLR, KDD, SIGIR, WWW etc.). • Knowledge of distributed training techniques, and efficiency at scale (memory, latency, hardware constraints).

🏖️ Benefits

• comprehensive medical coverage for you and your family • unlimited PTO • a 401(k) plan with matching • 12 weeks of paid parental leave • an Employee Stock Purchase Plan