Lead Machine Learning Engineer, Infrastructure

Upwork ($UPWK) is the world’s largest work marketplace, connecting businesses with highly skilled professionals worldwide. From entrepreneurs to Fortune 100 enterprises, companies trust Upwork’s platform to access expert talent, leverage AI-powered work solutions, and drive meaningful business outcomes.

Upwork’s AI-powered platform has facilitated over $20 billion in economic opportunity for professionals worldwide. With professionals spanning 10,000+ skills, including AI and machine learning, software development, sales and marketing, customer support, finance and accounting, and more, Upwork empowers businesses of all sizes to scale, innovate, and build agile teams.

The Machine Learning Infrastructure & Data team is responsible for architecting and building the foundational systems and tools that enable efficient development, deployment, and management of machine learning models at scale.

As a Lead Machine Learning Engineer in the Machine Learning Infrastructure & Data team, you will play a pivotal role in designing, developing, and maintaining robust and scalable infrastructure components to support the company's machine learning initiatives. You will collaborate closely with cross-functional teams including machine learning researchers, data scientists, and software engineers to build state-of-the-art platforms and tools that accelerate the development and deployment of machine learning models.

Key Responsibilities:

• Design, implement, and optimize distributed systems and infrastructure components to support large-scale machine learning workflows, including data ingestion, feature engineering, model training, and serving.
• Develop and maintain frameworks, libraries, and tools to streamline the end-to-end machine learning lifecycle, from data preparation and experimentation to model deployment and monitoring.
• Architect and implement highly available, fault-tolerant, and secure systems that meet the performance and scalability requirements of production machine learning workloads.
• Collaborate with machine learning researchers and data scientists to understand their requirements and translate them into scalable and efficient software solutions.
• Stay current with the latest advancements in machine learning infrastructure, distributed computing, and cloud technologies, and integrate them into our platform to drive innovation.
• Mentor junior engineers, conduct code reviews, and uphold engineering best practices to ensure the delivery of high-quality software solutions.

What it takes to catch our eye:

• Passion for ML Infrastructure: We value enthusiasm for advancing ML infrastructure.
• Proven Impact: Show us your track record of delivering impactful solutions.
• Innovative Thinker: Bring creativity and fresh ideas to the table.
• Technical Proficiency: Solid foundation in software engineering and ML concepts.
• Collaborative Mindset: Strong communication and teamwork skills are a must.
• Continuous Learner: Stay updated with the latest advancements in the field.
• Problem-Solving Skills: Ability to tackle complex problems effectively.
• Adaptability: Thrive in a fast-paced, dynamic environment.