Principal ML Infrastructure Engineer

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 ML systems and tools that enable efficient development, deployment, and management of machine learning models at scale.

As a Principal ML Infrastructure Engineer in the Machine Learning Infrastructure & Data team, you will play a pivotal role in designing, developing, and maintaining robust and scalable ML 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.

Responsibilities:

• Own technical workstreams from start to finish, contribute to the team’s product roadmap, and be responsible for major technical decisions and tradeoffs. Effectively participate in team’s planning, code reviews, and design discussions
• Consider the effects of projects across multiple teams and proactively manage conflicts. Work together with partner teams to achieve cross-departmental goals and satisfy broad requirements
• 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, model training, evaluation, 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 and publish with machine learning researchers and data scientists on novel research and translate research 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 teammates, conduct code reviews, and uphold engineering best practices to ensure the delivery of high-quality software solutions.

What it takes to catch our eye:

• Senior/Leadership level experience in ML infrastructure engineering, ideally at an innovative technology company.
• 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 of AI.
• Our Team's Tech stack: Compute: AWS, EKS, Databricks - Data: Snowflake, S3, SQLMesh, Feast - Workflow Automation: Airflow - Experiment Tracking: Weights & Biases, MLflow -  LLM Inference: Fireworks, in-house deployment on EKS

Come change how the world works.

At Upwork, you’ll shape talent solutions for how the world works today. We are a remote-first organization working together to create exciting remote work opportunities for a global community of professionals. While we have physical offices in San Francisco and Chicago, currently we also hire full-time employees in 19 states in the United States. 

At the core of our vibrant culture are shared values that form the foundation of our organization. These values revolve around trust, risk-taking, customer focus, and excellence. Our overarching mission is to create economic opportunities so that people have better lives. We foster an environment where individuals are encouraged to bring their authentic selves to work, nurturing personal and professional growth through development opportunities, mentorship programs, and participation in Upwork Belonging Communities.

We take pride in providing exceptional benefits to our employees. These include comprehensive medical insurance coverage for both you and your family, unlimited paid time off, a 401(k) plan with matching contributions, 12 weeks of paid parental leave, and an Employee Stock Purchase Plan. To explore these benefits in detail, as well as gain insights into our company values, working principles, and the overall employee experience, we invite you to visit our Life at Upwork page.

Check out our Careers page to learn more about the employee experience.   

Upwork is proudly committed to recruiting and retaining a diverse and inclusive workforce. As an Equal Opportunity Employer, 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.

The annual base salary range for this position  is displayed below. The range displayed reflects the minimum and maximum salary for this position, and individual base pay will depend on your skills, qualifications, experience, and location. Additionally, this position is eligible for the annual bonus plan or sales incentive plan and eligibility to participate in our long term equity incentive program.

Annual Base Compensation

$216,500 - $390,750 USD

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