1.65 Senior Machine Learning Platform Engineer in Irvine

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Job DescriptionJob DescriptionWho are We?
Field AI is transforming how robots interact with the real world. We are building risk-aware, reliable, and field-ready AI systems that address the most complex challenges in robotics, unlocking the full potential of embodied intelligence. We go beyond typical data-driven approaches or pure transformer-based architectures, and are charting a new course, with already-globally-deployed solutions delivering real-world results and rapidly improving models through real-field applications. Learn more at https://fieldai.com.
About the Job
Our Field Foundation Model (FFM) powers a global fleet of autonomous robots that capture massive streams of multimodal data across diverse, dynamic environments every day. As part of the Insight Team our mission is to transform this raw, multimodal data into actionable insights that empower our customers and engineers to deliver value. Field-insight Foundation Model (FiFM) is at the core of how we transform multimodal data from autonomous robots into actionable insights. As a Senior Machine Learning Platform Engineer, you will own the infrastructure that powers FiFM, from model hosting and distributed training pipelines to data systems, observability, and security.This is a role at the intersection of systems engineering and machine learning. You’ll design and operate large-scale ML platforms, ensure FiFM transitions smoothly from research into production, and optimize for both performance and cost across cloud and edge. In addition to building core infrastructure, you’ll play a leadership role by mentoring junior engineers, setting technical direction, and raising the engineering bar across the team.What You’ll Get To Do:

• Design and manage scalable ML infrastructure with IaC tools (Terraform, CloudFormation).
• Develop and optimize cloud-based pipelines for training, evaluation, and inference on multimodal datasets.
• Build and operate data systems for large-scale video ingestion, indexing, and storage.
• Maintain MLOps workflows for versioning, experiment tracking, reproducibility, and CI/CD.
• Ensure reliability and observability with monitoring, logging, and alerting.
• Collaborate with AI/ML Engineers to productionize workflows.
• Optimize infrastructure for performance and cost across cloud and edge.
• Enforce best practices in security, compliance, and maintainability.
• Mentor and manage junior engineers, providing technical guidance and career development.

What You Have:

• Bachelor’s/Master’s in Computer Science, Engineering, or related field (or equivalent experience).
• 4+ years of industry experience in ML infrastructure or platform engineering.
• Strong coding skills in Python/TypeScript and a strong foundation in software engineering best practices.
• Proven experience with distributed systems, cloud platforms (AWS preferred), containerization and orchestration (Docker, Kubernetes/EKS, Ray), and serverless.
• Hands-on experience building ML pipelines for distributed training and large-scale inference.
• Strong knowledge of data management at scale, including preprocessing and retrieval of video/image datasets.
• Proficiency with CI/CD pipelines, infrastructure-as-code (Terraform, CloudFormation), and automation.
• Familiarity with MLOps tools (MLflow, Kubeflow, Airflow).
• Experience with system monitoring and observability in production.

The Extras That Set You Apart:

• Experience with vector databases (OpenSearch, Pinecone, Weaviate) for indexing and retrieval.
• Familiarity with distributed training frameworks (Horovod, DDP/FSDP, DeepSpeed, Ray).
• Hands-on experience with GPU orchestration and auto-scaling (Karpenter, SageMaker, EKS).
• Experience with agentic AI deployment workflows, orchestration frameworks, and retrieval-augmented .
• Strong knowledge of security and compliance in ML and cloud environments.

Compensation and Benefits
Our salary range is generous ($70,000 - $200,000 annual), but we take into consideration an individual's background and experience in determining final salary; base pay offered may vary considerably depending on geographic location, job-related knowledge, skills, and experience.  Also, while we enjoy being together on-site, we are open to exploring a hybrid or remote option.
Why Join Field AI?
We are solving one of the world’s most complex challenges: deploying robots in unstructured, previously unknown environments. Our Field Foundational Models™ set a new standard in perception, planning, localization, and manipulation, ensuring our approach is explainable and safe for deployment.You will have the opportunity to work with a world-class team that thrives on creativity, resilience, and bold thinking. With a decade-long track record of deploying solutions in the field, winning DARPA challenge segments, and bringing expertise from organizations like DeepMind, NASA JPL, Boston Dynamics, NVIDIA, Amazon, Tesla Autopilot, Cruise Self-Driving, Zoox, Toyota Research Institute, and SpaceX, we are set to achieve our ambitious goals.
Be Part of the Next Robotics Revolution
To tackle such ambitious challenges, we need a team as unique as our vision — innovators who go beyond conventional methods and are eager to tackle tough, uncharted questions. We’re seeking individuals who challenge the status quo, dive into uncharted territory, and bring interdisciplinary expertise. Our team requires not only top AI talent but also exceptional software developers, engineers, product designers, field deployment experts, and communicators.We are headquartered in always-sunny Mission Viejo (Irvine adjacent), Southern California and have US based and global teammates. 
Join us, shape the future, and be part of a fun, close-knit team on an exciting journey!
We celebrate diversity and are committed to creating an inclusive environment for all employees. Candidates and employees are always evaluated based on merit, qualifications, and performance. We will never discriminate on the basis of , color, , , , veteran status, status, , , , martial status, mental or physical , or any other legally protected status.

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