Founding Forward Deployed Engineer (FDE) focused on bridging cutting-edge AI research, robotics data infrastructure, and real-world customer deployments.
Responsibilities
Own End-to-End Technical Delivery: Lead customer engagements from requirements gathering and technical scoping through implementation, validation, and delivery.
Serve as a Technical Partner: Work directly with customers to understand their robotics, AI model training, and data infrastructure needs, troubleshoot issues, and drive successful outcomes.
Build and Improve Data Infrastructure: Develop and optimize data pipelines, integrations, and workflows supporting large-scale robotics and multimodal AI datasets.
Drive Product Improvements: Translate customer feedback and technical challenges into actionable improvements for internal engineering and platform teams.
Develop Scalable Solutions: Build reusable tools, automation, and technical processes to improve delivery efficiency and customer experience.
Lead the design and development of our production inference platform, define the technical roadmap for inference infrastructure, build and operate scalable, cost-effective systems for serving large language models in production, evaluate and integrate modern inference technologies, optimize latency, throughput, GPU utilization, memory efficiency, and infrastructure cost, develop systems for model deployment, traffic routing, autoscaling, scheduling, observability, and operational excellence, partner with ML engineers to productionize new models and inference techniques, establish benchmarking methodologies, make key architectural decisions, mentor engineers and help establish engineering best practices for AI infrastructure.
Compensation
Salary Range ($190- $230K) plus health insurance and equity. United States - Remote Pay Range $190,000—$230,000 USD
Responsibilities
Lead the design and development of our production inference platform.
Define the technical roadmap for inference infrastructure, model serving, and runtime optimization.
Build and operate scalable, cost-effective systems for serving large language models in production.
Evaluate and integrate modern inference technologies, frameworks, and serving runtimes.
Optimize latency, throughput, GPU utilization, memory efficiency, and infrastructure cost.
Lead end-to-end systems engineering for ZipRecruiter’s Job Seeker Apps, driving AI integration, product strategy, and technical mentorship across data engineering, backend infrastructure, and full-stack integration.
Locations (2)
Santa Monica, California, United States
United States
Compensation
The US base salary range for this full-time position is $195,000 - $255,000. Our salary ranges are determined by role, level, and location, and the range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location, role-related knowledge and skills, depth of experience, relevant education or training, and additional role-related considerations. Depending on the position offered, equity, bonuses, commission, or other forms of compensation may also be provided as part of a total compensation package, in addition to a full range of medical, financial, and other benefits.
Responsibilities
Operate across multiple problem spaces—from data engineering to backend infrastructure and full-stack integration.
Partner closely with Product Management and Decision Science to inject engineering perspectives early in the product development lifecycle.
Act as a technical anchor, up-leveling an engineering team, guiding ICs, and keeping Engineering Managers aligned on technical execution.
Design and implement creative, data-driven methods to measure the real-world success of newly shipped user-facing features.
Architect how ZipRecruiter is presented in AI assistants and agentic systems, with the measurement and guardrails to run those integrations safely at scale.
Requirements
BS/MS/PhD in Mathematics, Computer Science, Physics, related technical field or equivalent practical experience
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