Role: Lead AI Engineer, ML Systems
Location: Palo Alto, CA (Hybrid)
Duration: Full-time / Direct Hire
 
About the Role
We are seeking a Lead AI Engineer, ML Systems to join the AI Research Incubation Team.
 
In this role, you will own the engineering systems that power model inference, fine-tuning, and evaluation, enabling research models to be reliably deployed and evolved in production environments.
 
You will work closely with AI researchers, agent engineers, and platform teams to support model serving, LoRA-based fine-tuning workflows, and model lifecycle management. This role focuses on production ML systems, not on inventing new model architectures.
 
This is a lead-level individual contributor role with deep ownership of model-facing systems and strong cross-team influence.
 
Key Responsibilities

• Design, build, and maintain model inference and serving systems, including integration with AI gateways.
• Own and evolve fine-tuning pipelines (e.g., LoRA / PEFT) using internal model tooling.
• Develop and maintain model evaluation, regression detection, and rollout workflows.
• Collaborate with AI researchers to transition research models into production-ready assets.
• Optimize inference systems for latency, throughput, stability, and cost efficiency.
• Implement best practices for model versioning, deployment, rollback, and monitoring.
• Partner with agent and platform engineers to ensure smooth integration between model systems and agent runtimes.
• Provide technical leadership and mentorship on ML system design and operational excellence.

Required Qualifications

• Bachelor’s degree in Computer Science, Software Engineering, or a related field.
• 5+ years of experience in software engineering, with significant ownership of backend or distributed systems.
• Strong proficiency in Python, with experience building production services.
• Hands-on experience with AI/ML model serving, inference pipelines, or ML systems engineering.
• Experience designing reliable, scalable systems for production environments.
• Familiarity with cloud platforms (AWS, GCP) and containerized environments (Docker, Kubernetes).
• Strong debugging skills across system, data, and model-facing failures.
• Excellent communication skills and ability to collaborate across research and engineering teams.

Preferred Qualifications

• Experience with fine-tuning techniques such as LoRA or PEFT.
• Familiarity with model evaluation frameworks and regression testing.
• Experience with GPU-based workloads or ML infrastructure.
• Knowledge of data formats and pipelines commonly used in ML systems.
• Prior experience working closely with AI research or incubation teams.

 
 
At SPECTRAFORCE, we are committed to maintaining a workplace that ensures fair compensation and wage transparency in adherence with all applicable state and local laws. This position’s starting pay is: $ 185000.00/Yearly.