Software Engineer (Junior & New Grad ML Infrastructure)
Posted Updated
- We’re hiring a Machine Learning Infrastructure Engineer to help build the backbone that trains, serves, and monitors the models behind our Ads and Recommendations products
- You’ll join a small, high-ownership team that ships platform improvements end-to-end—partnering with product and data teams, reducing latency and cost, and shortening the path from an idea to a safely launched model
- You’ll work across the ML lifecycle: making training faster and more reliable, improving model serving performance, and strengthening our feature/embedding platform so models stay fresh and consistent between offline and online use
- Scope & impact: small team, big surface area—your work lands directly in production
- Ownership: from design to rollout to post-launch learnings; real autonomy with support
- Growth: visibility across the stack and a clear path to lead projects and mentor others
- Pragmatic culture: we optimize for outcomes over buzzwords, and we value clear thinking, and follow-through
- You’ll design and develop machine learning infrastructure
- Own and enhance core components of the ML infrastructure, including systems for offline and online model training, model pipeline health monitoring, model serving, feature authoring, and feature serving
- Proactively address ML infrastructure issues that may impact production
- Collaborate with ML engineers to build robust model pipelines utilizing the ML infrastructure
Benefits
- Work from home opportunities
- Paid time off and paid holidays
- Paid parental leave
- FSA and commuter benefit programs
- Team activity budget
- Top-tier 401(K) plan with company matching
- Health, dental, and vision care for you and your family
- We’re looking for someone who can take real ownership, finish what’s started, and raise the bar on stability and developer experience
- You like building reliable systems that make ML teams move faster—and you enjoy turning complexity into simple, durable solutions
- Bachelor’s degree in Computer Science, Engineering, or a related field with 2+ years of relevant work experience; or a Master’s/PhD in a related discipline
- Familiarity with software development processes, including version control, bug tracking, and design documentation
- Basic knowledge of Applied Machine Learning and experience with major Deep Learning frameworks, such as PyTorch and TensorFlow
- Proficient in Python, with a strong understanding of object-oriented languages such as C++ or Java
- A systematic, data-driven problem-solving approach combined with strong communication skills
- Contributions to open-source machine learning or infrastructure tools
- Familiarity with cloud services such as AWS, GCP, Azure, and others