Senior ML Ops Engineer at parallel

Setup: Hybrid
Location: Los Angeles, California
Level: not_specified
Posted: Jul 28, 2026

Description

Parallel Systems is looking for an experienced Senior ML Ops Engineer to design and develop scalable systems for their autonomy and perception pipelines. This role involves leading the ML infrastructure stack, managing distributed training and deployment, collaborating with engineering teams, and optimizing cloud-based systems for ML workloads.

Required Skills

MLOps Solutions
Automated Pipelines
Data Management
Model Training
Deployment
Monitoring
Scalable ML Infrastructure
Distributed Training
Inference
Cloud-Based Systems
AWS
GCP
Continuous Integration/Deployment
Experiment Management
Governance of Models and Datasets
Automation of Model Evaluation
Selection, and Deployment Workflows

Additional Information

Required Previous Experiences: Experience in 0 to 1 builds of perception systems.
Preferred Qualifications: Deep understanding of the product goals, existing infrastructure, and stakeholder requirements.
Conducted technical discovery and proposed a preliminary MLOps architecture—evaluating various ML tools, cloud services, and workflow strategies—clearly outlining pros and cons for each option.
Delivered a detailed design document that outlines the end-to-end ML pipeline, including data ingestion, model training, deployment, and monitoring.
Iterated on the design and built PoC for the core ML workflow aligned with the approved architecture.
Initiated the implementation of the remaining features, ensuring the infrastructure supports scalable, repeatable workflows for model experimentation and deployment in both R&D and production environments.