Parallel · 20 hours ago
Senior ML Ops Engineer (Machine Learning Infrastructure)
Los Angeles, CA
Full-time
Hybrid
Senior Level
$150K/yr - $240K/yr
5+ years expParallel Systems is pioneering autonomous battery-electric rail vehicles designed to transform freight transportation by shifting portions of the $900 billion U.S. trucking industry onto rail. They are seeking an experienced MLOps/ML Infrastructure Engineer to lead the design and development of scalable systems that power their autonomy and perception pipelines.
CannabisHealth CarePersonal HealthTherapeuticsWellness
Responsibilities
Design and implement robust MLOps solutions, including automated pipelines for data management, model training, deployment and monitoring
Architect, deploy, and manage scalable ML infrastructure for distributed training and inference
Collaborate with ML engineers to gather requirements and develop strategies for data management, model development and deployment
Build and operate cloud-based systems (e.g., AWS, GCP) optimized for ML workloads in R&D, and production environments
Build scalable ML infrastructure to support continuous integration/deployment, experiment management, and governance of models and datasets
Support the automation of model evaluation, selection, and deployment workflows
Qualification
Required
Bachelor's or higher degree in Computer Science, Machine Learning, or a relevant engineering discipline
5+ years of experience building large-scale, reliable systems; 2+ years focused on ML infrastructure or MLOps
Proven experience architecting and deploying production-grade ML pipelines and platforms
Strong knowledge of ML lifecycle: data ingestion, model training, evaluation, packaging, and deployment
Hands-on experience with MLOps tools (e.g., MLflow, Kubeflow, SageMaker, Airflow, Metaflow, or similar)
Deep understanding of CI/CD practices applied to ML workflows
Proficiency in Python, Git, and system design with solid software engineering fundamentals
Experience with cloud platforms (AWS, GCP, or Azure) and designing ML architectures in those environments
Preferred
Experience with deep learning architectures (CNNs, RNNs, Transformers) or computer vision
Hands-on experience with distributed training tools (e.g., PyTorch DDP, Horovod, Ray)
Background in real-time ML systems and batch inference, including CPU/GPU-aware orchestration
Previous work in autonomous vehicles, robotics, or other real-time ML-driven systems
Company
Parallel
Parallel cultivates, produces, and processes cannabis for medical purposes.
1001-5000 employees
H1B Sponsorship
Parallel has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2024 (3)
2023 (1)
2020 (1)
Funding
Current Stage
Late StageTotal Funding
$365.74MKey Investors
SunStreamEdward Brown
2022-12-08Debt Financing· $10M
2021-01-01Series Unknown
2019-06-27Series D· $100M
Leadership Team
Barry Jones
Chief Financial Officer
Lynnette F.
Chief Operating Officer
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