Staff Software Engineer, AI Foundation Model

Role Overview

• Technically strategize on Foundation model selection, refactor, design, build, and maintain Merlin's core AI models, training and inference infrastructure, including distributed training pipelines, experiment tracking, and model registry systems.
• Define and drive standards and benchmarks for model evaluation, benchmarking, and regression testing to ensure AI systems meet safety and performance thresholds before deployment.
• Architect and own the foundational data pipeline that ingests, processes, labels, and versions flight data for use across all autonomy and AI teams.
• Identify and resolve systemic technical bottlenecks that slow down AI development velocity across Merlin's engineering organization.
• Collaborate with AI infra, Simulation, and Flight Software teams to define interfaces and shared abstractions that make the broader stack more coherent and maintainable.
• Mentor, build and technically guide junior and mid-level engineers on the AI Foundation team, conducting design reviews and raising the overall quality of the team's output.
• Lead technical scoping and estimation for large AI foundational model projects, breaking ambiguous requirements into actionable engineering plans.
• Evaluate and adopt relevant open-source tooling, frameworks, and research, contributing back where appropriate.
• Document architecture decisions, system designs, and operational runbooks to a standard that supports safety review and long-term maintainability.
• Contribute to hiring by conducting technical interviews and helping define the engineering bar for the AI Foundation team.

Requirements

• 8+ years of software engineering experience, with a substantial portion focused on state of the art and next-gen AI model development, ML infrastructure, MLOps, data engineering, or AI platform development.
• Experience in development of the AI-first Autonomy software tech stack that includes Perception, Behavior Planning, Prediction and Actuation ( based on Transformer architectures)
• Demonstrated ability to design and deliver large-scale, production-grade systems independently — from initial architecture through deployment and operation.
• Deep proficiency in Pytorch, TensorFlow and at least one systems language such as C++, C, Rust, or Go.
• Hands-on experience with distributed training frameworks (Python extensions, JAX, or equivalent) and the infrastructure required to run them reliably at scale.
• Experience in onboarding trained models into edge environments consisting of High performance compute System-on-Chips.
• Strong background in data pipeline design, including streaming and batch processing, data versioning, and handling high-volume, heterogeneous sensor data.
• Experience building model evaluation and validation frameworks leveraging MLOps frameworks (like Weights and Biases. MLFlow etc) that go beyond accuracy metrics to assess real-world reliability and safety-relevant behavior.
• Proven track record of influencing technical direction across teams and driving alignment on shared infrastructure and standards.
• Excellent written communication skills, with the ability to produce clear design documents and architecture proposals that hold up to rigorous review.
• Comfort working in a fast-moving startup where the scope of problems and priorities evolve as the product matures.

Tech Stack

• Python
• PyTorch
• Rust
• Tensorflow
• Go

Benefits

• catered lunches featuring a rotating menu of delicious options
• an assortment of snacks to keep you fueled throughout the day
• a selection of beverages, including coffee, tea, and other drinks, to keep you refreshed.
• top-notch benefits package (health, dental, life, unlimited vacation, and 401k with match)
• professional development