Senior ML Ops Engineer (Machine Learning Infrastructure) jobs in United States
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Parallel · 9 hours ago

Senior ML Ops Engineer (Machine Learning Infrastructure)

Parallel Systems is pioneering autonomous battery-electric rail vehicles designed to transform freight transportation. 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.

Autonomous VehiclesFreight ServiceGreenTechTransportation
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H1B Sponsor Likelynote

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

ML infrastructureMLOps toolsCloud platformsPythonCI/CD practicesDistributed trainingSoftware engineeringCollaborationProblem-solving

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

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Parallel develops autonomous, battery-electric rail vehicles to convert freight from truck to rail.

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
2025 (2)
2024 (3)
2023 (3)
2022 (1)

Funding

Current Stage
Growth Stage
Total Funding
$91.35M
Key Investors
Anthos CapitalCongruent Ventures
2025-04-14Series B· $38M
2022-01-19Series A· $49.55M
2020-06-22Seed· $3.8M

Leadership Team

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Matt Soule
CEO and Co-Founder
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Benjamin Stabler
Co-Founder, VP of Engineering
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Company data provided by crunchbase