Staff Software Engineer

About the Team:

The ML Reliability team at Liftoff is dedicated to building and maintaining tools that ensure the robustness, observability, and performance of machine learning systems at scale. As part of a cross-functional engineering org, the team focuses on enabling high-quality ML operations by providing observability into data and model pipelines, enforcing safeguards against misconfigurations, and defining best practices for integrating new features, models, and data sources. This role plays a key part in advancing that mission, helping shape the reliability platform that supports Liftoff’s ML-driven products and ensures consistent and dependable outcomes in production.

AS A BACKEND ENGINEER ON THE ML PLATFORM TEAM, YOU WILL:

• Lead the design and evolution of large-scale ML infrastructure, driving improvements in availability, reliability, and operational excellence for our production ML systems.
• Define and implement end-to-end monitoring, alerting, and performance tracking for ML models and data pipelines, ensuring model health and data integrity at scale.
• Partner with data scientists and platform teams to standardize and scale model deployment, versioning, and A/B experimentation frameworks.
• Lead and participate in incident response efforts, conducting root cause analysis and implementing corrective actions to prevent recurrence.
• Identify systemic inefficiencies and opportunities for automation or simplification, and drive cross-functional efforts to improve system performance and developer productivity.
• Drive adoption of best practices in software and ML engineering, including code quality, risk-driven testing, and explainable, maintainable systems.
• Act as a mentor and multiplier, helping other engineers level up in ML systems, reliability, and architectural thinking..
• Contribute to strategic planning and partner with product and platform leads to align engineering efforts with business outcomes.

DESIRED QUALITIES AND EXPERIENCES:

• BS in Computer Science with 8+ years of professional experience; or
• MS in Computer Science with 6+ years of professional experience; or
• PhD with 3+ years of professional experience; software engineering, or reliability engineering, with a focus on production systems.
• Proven ability to drive large technical initiatives and lead projects spanning multiple teams.
• Solid core CS fundamentals (data structures, algorithms, architecting systems).
• Deep expertise in Python and/or Go; fluency with ML libraries (e.g., TensorFlow, PyTorch), cloud infrastructure (e.g., AWS)
• Experience with ML monitoring tools (e.g. Prometheus, Grafana).
• Experience in big data engines such as Trino and Spark is a big plus.
• Excitement to work on cutting-edge ML infrastructure at massive scale—and to make it simple, reliable, and elegant.
• Strong problem-solving skills and the ability to work collaboratively across teams.
• Ability to lead across team and role boundaries to effect large scale change in culture and systems.
• A healthy sense of fun!

NICE TO HAVE:

• Experience in ML systems for training Transformer models, CTR prediction models.
• Prior experience in AdTech, mobile growth, or performance marketing domains.
• Contributions to open-source ML infrastructure or tools.

Location:
This role is eligible for full-time remote work in one of our entities: CA, CO, ID, IL, FL, GA, MA, MI, MN, MO, NJ, NV, NY, OR, PA, TX, UT, WA, and Canada.

We are a remote-first company with US hubs in Redwood City, Los Angeles, and New York City.

Travel Expectations:
We offer several opportunities for in-person team gatherings, including but not limited to project meetings, regional meetups, and company-wide events. We expect our employees to attend these gatherings at least once per quarter. These gatherings provide essential opportunities for collaboration, communication, and team building.

Compensation:
Liftoff offers all employees a full compensation package that includes equity and health/vision/dental benefits associated with your country of residence. Base compensation will vary based on the candidate's location and experience.

The following are our base salary ranges for this role: 

• Canada: CAD 150,000 - 185,000

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