Senior Machine Learning Infrastructure Engineer

PlusAI

Santa Clara (CA)

On-site

USD 160,000 - 200,000

Full time

14 days+

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Benefits offered by this job

Catered free lunch

Unlimited snacks and beverages

401(k) plan

Competitive salary and benefits package

Job summary

PlusAI, based in Silicon Valley, is seeking a Senior ML Infrastructure Engineer to design scalable architectures for machine learning models. This role involves building robust data pipelines, managing GPU clusters, and collaborating with cross-functional teams. Candidates should have a PhD or MS in a relevant field and experience in software engineering, specifically in ML infrastructure. The position offers a competitive salary between $160,000 and $200,000 along with other benefits including a 401(k) plan.

Qualifications

3+ years of software engineering experience focused on ML infrastructure or distributed systems.
Good oral and written communication skills.
Ability to learn and adapt to new technologies.

Responsibilities

Design and develop scalable systems for training and deploying ML models.
Build and maintain efficient data pipelines and model versioning systems.
Collaborate with teams to improve platform usability.
Implement distributed systems and storage solutions.
Ensure high availability of the ML platform with monitoring systems.
Mentor junior engineers.

Skills

Python

C++

SQL

Docker

Kubernetes

Deep learning frameworks (PyTorch, TensorFlow)

Cloud platforms (AWS, GCP)

Distributed systems

Experiment tracking tools (Kubeflow, mlflow)

Software design and development

Education

PhD or MS in Computer Science, Electrical Engineering, or related field

Tools

Apache Airflow

Prefect

Job description

PlusAI is a Physical AI company pioneering AI-based virtual driver software for factory-built autonomous trucks. Headquartered in Silicon Valley with operations in the United States and Europe, Plus was named by Fast Company as one of the World’s Most Innovative Companies. Partners including TRATON GROUP’s Scania, MAN, and International brands, Hyundai Motor Company, Iveco Group, Bosch, and DSV are working with Plus to accelerate the deployment of next-generation autonomous trucks. If you’re ready to make a huge impact and drive the future of autonomy, Plus is looking for talented individuals to join its fast-growing teams.

As a Senior ML Infrastructure Engineer at Plus, you will design scalable architectures capable of handling petabytes of data while ensuring optimal performance for both training and inference phases. You will build robust pipelines for managing model versioning systems and experiment tracking frameworks, which are essential for maintaining reproducibility across experiments. Additionally, you will be responsible for managing large-scale GPU clusters. This role offers unparalleled opportunities—both technically and professionally—for individuals passionate about solving challenging problems using modern cloud-native technologies. Ideal candidates thrive in environments that leverage tools such as Docker containers orchestrated via Kubernetes clusters, seamlessly integrated with state-of-the‑art deep learning frameworks like PyTorch or TensorFlow. If you are eager to push the boundaries of what's possible in machine learning infrastructure and contribute to cutting‑edge solutions, this position is an excellent fit!

Responsibilities

Design and develop scalable, high‑performance systems for training, inference, deploying, and monitoring ML models at scale.
Build and maintain efficient data pipelines, model versioning systems, and experiment tracking frameworks.
Collaborate with cross‑functional teams, including ML researchers and engineers, to identify bottlenecks and improve platform usability.
Implement distributed systems and storage solutions optimized for machine learning workloadsDrive improvements in CI/CD workflows for ML models and infrastructure.
Ensure high availability and reliability of the ML platform by implementing robust monitoring, logging, and alerting systems.
Stay current with industry trends and integrate relevant tools and frameworks to enhance the platform.
Mentor junior engineers and contribute to a culture of technical excellence
Ensure that your work is performed in accordance with the company’s Quality Management System (QMS) requirements and contribute to continuous improvement efforts.
Ensure team compliance with QMS, monitor quality, and drive process improvements.

Required Skills

Phd or MS in Computer Science, Electrical Engineering, or related field
Good oral and written communication skills
Phd new grad or Masters with 3+ years of software engineering experience with a focus on ML infrastructure or distributed systems.
Proficiency in in Python, C++, SQL
Deep understanding of containerization, orchestration technologies, distributed ML workload, and experiment tracking tools (e.g., Docker, Kubernetes, multiprocessing, Kubeflow, and mlflow)
Deploy and manage resources across multiple cloud platforms (AWS, GCP, or on‑prem environments)
Proficiency in at least one deep learning framework, such as PyTorch and data pipeline tools (e.g., Apache Airflow, Prefect).
Strong knowledge of distributed systems, databases, and storage solutions.
Extensive software design and development skills.
Ability to learn and adapt to new technologies and contribute in a productive environment.

Preferred Skills

Familiarity with fundamental deep learning architectures, such as Convolutional Neural Networks (CNNs) and Transformer models
Experience in building large‑scale ML datasets, MLOps pipelines, and distributed computing frameworks like Ray
Experience working with autonomous vehicles or robotics

Salary Range