Senior Applied Machine Learning Engineer - Search & Recommendations

Upwork; Remote; CAD 100,000 - 130,000; Full time

Job summary

A leading technology company in Toronto, Canada, is looking for a Senior Applied Machine Learning Engineer. This role involves leveraging advanced machine learning techniques to develop solutions impacting a global platform. Candidates should have a strong background in ML, data analysis, and programming languages like Python and SQL. This position offers great opportunities for professional growth while working remotely with a diverse team.

Qualifications

• 3+ years of relevant industry experience building large scale ML systems.
• Prior experience with large language models or agentic AI.
• Clear track record of publications in peer‑reviewed conferences.

Responsibilities

• Analyze structured and unstructured data for insights to improve model performance.
• Design and implement features and models for machine learning applications.
• Collaborate with other teams to share insights and recommend improvements.

Skills

Machine Learning

Data Analysis

Python

SQL

PyTorch

TensorFlow

Education

Masters/PhD in Computer Science or related field

Tools

Large Language Models

Distributed Training Techniques

Job description

Upwork Inc.’s (Nasdaq: UPWK) family of companies connects businesses with global, AI-enabled talent across every contingent work type including freelance, fractional, and payrolled. This portfolio includes the Upwork Marketplace, which connects businesses with on-demand access to highly skilled talent across the globe, and Lifted, which provides a purpose-built solution for enterprise organizations to source, contract, manage, and pay talent across the full spectrum of contingent work. From Fortune 100 enterprises to entrepreneurs, businesses rely on Upwork Inc. to find and hire expert talent, leverage AI-powered work solutions, and drive business transformation. With access to professionals spanning more than 10,000 skills across AI & machine learning, software development, sales & marketing, customer support, finance & accounting, and more, the Upwork family of companies enables businesses of all sizes to scale, innovate, and transform their workforces for the age of AI and beyond.

Since its founding, Upwork Inc. has facilitated more than $30 billion in total transactions and services as it fulfills its purpose to create opportunity in every era of work. Learn more about the Upwork Marketplace at Upwork.com.

Are you passionate about using machine learning to drive meaningful change? As a Senior Applied Machine Learning Engineer at Upwork, you will leverage advanced machine learning techniques to deliver cutting-edge solutions that directly impact our global platform and user experience. You’ll work with large-scale data to solve complex problems, from improving search relevance to personalizing recommendations, and create a powerful, seamless experience for our users. This is a unique opportunity to contribute to the innovation at the world’s largest work marketplace, where your work will enable our community of freelancers and clients to connect and collaborate in impactful ways.

Responsibilities

• 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

What it takes to catch our eye

• 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)

Come change how the world works

This position will initially be employed through a partner to ensure a seamless hiring process while we establish the hub. Once the hub is established, there may be opportunities to transition to employment with Upwork depending on business needs and other requirements. While employed by the partner, you’ll work as part of Upwork’s team, with access to our resources, culture, and growth opportunities.

Upwork is an Equal Opportunity Employer committed to recruiting and retaining a diverse and inclusive workforce. We do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, or other legally protected characteristics under federal, state, or local law.

Please note that a criminal background check may be required once a conditional job offer is made. Qualified applicants with arrest or conviction records will be considered in accordance with applicable law, including the California Fair Chance Act and local Fair Chance ordinances. The Company is committed to conducting an individualized assessment and giving all individuals a fair opportunity to provide relevant information or context before making any final employment decision.

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