Upwork ($UPWK) is the world’s work marketplace. We serve everyone from one-person startups to over 30% of the Fortune 100 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 $3.3 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.
This is an engagement through Upwork’s Hybrid Workforce Solutions (HWS) Team. Our Hybrid Workforce Solutions Team is a global group of professionals that support Upwork’s business. Our HWS team members are located all over the world.
This role is a long-term contract position.
We are looking for a highly skilled Senior Machine Learning Ops Engineer to join our Algorithms and Research team. This role is perfect for someone who thrives on productizing advanced technologies like Generative AI and who is excited to revolutionize search and recommendation technologies at scale. Join us in innovating at the intersection of machine learning, knowledge graphs, and retrieval-augmented generation (RAG) to make a significant impact on the Upwork platform and our global community of users.
Key Responsibilities:
- Deploy, scale, and maintain machine learning and ETL pipelines within the context of production Generative AI and Large Language Models.
- Design, develop, and optimize retrieval-augmented generation systems, leveraging knowledge graphs to significantly enhance search accuracy and recommendations.
- Implement robust machine learning monitoring and alerting systems; integrate these with active learning pipelines for continuous model improvement.
- Collaborate cross-functionally to ensure smooth integration of machine learning solutions into Upwork’s global platform.
- Continuously analyze, monitor, and optimize model performance, accuracy, and scalability, ensuring consistent reliability during high-traffic periods.
Must Haves (Required Skills):
- 6+ years of proven professional experience in machine-learning operations and software engineering.
- Demonstrated success in deploying and scaling complex machine-learning models into production.
- Strong expertise in Python, particularly focused on data and ML pipelines.
- Experience with both batch and real-time ETL tooling
- Solid proficiency in Java, especially in building and maintaining high-traffic microservices.
- Deep familiarity with graph databases, graph data models (e.g., labeled property graph), and graph algorithms.
- Extensive experience building scalable distributed systems capable of handling at least 1000 requests per second during peak usage.
- Proficiency in cloud infrastructure technologies, specifically AWS; familiarity with GCP and Azure will also be considered highly transferable.
- Familiarity with Generative AI technologies and Large Language Models.
- Excellent analytical thinking, problem-solving skills, and a proactive, innovation-driven approach.
- Proven ability to excel in a remote-first, collaborative team environment.
- A “zero-to-one” mindset: comfortable navigating ambiguity, driving solutions from conceptualization to execution, and thriving in a fast-paced, startup-like environment within a larger enterprise.
- Pragmatic, results-oriented, and driven to iterate rapidly to achieve measurable outcomes.
Upwork is proudly committed to fostering a diverse and inclusive workforce. We never discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical condition), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.
Additionally, a criminal background check may be run on a candidate after a conditional offer to perform your services for Upwork 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.
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