Machine Learning Platform Engineer, Machine Learning (ML) and Artificial Intelligence (AI) Required, Work From Home

Machine Learning Platform Engineer Machine Learning (ML) and Artificial Intelligence (AI) Required Work From Home

As the Machine Learning Platform Engineer you will build the infrastructure and systems that power Artificial Intelligence (AI) capabilities.  You will design and operate the systems behind the Artificial Intelligence (AI) stack from model training and evaluation to deployment inference observability and continuous improvement.  You will work closely with Artificial Intelligence (AI) engineers researchers and product engineers to turn models into reliable scalable and cost-efficient production systems.  You will build the platforms tooling and infrastructure that enable the team to experiment quickly and bring AI capabilities to production with confidence.  Machine Learning (ML) and Artificial Intelligence (AI) experience are required.  This position is 100% Remote.

MUST BE WILLING TO TAKE A 60 MINUTE CODING ASSESSMENT.

Machine Learning Platform Engineer Responsibilities:

- Build and operate the Machine Learning (ML) infrastructure and platforms powering Artificial Intelligence (AI) products.

- Design systems for model training evaluation deployment inference and experimentation.

- Build and optimize model serving and inference infrastructure for high-throughput and low-latency workloads.

- Improve reliability scalability latency and cost efficiency of Artificial Intelligence (AI) systems.

- Develop reliable pipelines for data preparation training evaluation model release and continuous improvement.

- Build platforms and tooling that enable Artificial Intelligence (AI) engineers and researchers to experiment evaluate and ship models faster.

- Develop evaluation and benchmarking infrastructure to measure model quality performance and regressions.

- Build production observability monitoring tracing and alerting for Artificial Intelligence (AI)/Machine Learning (ML) workloads.

- Improve Artificial Intelligence (AI) systems across reliability scalability latency throughput and cost.

- Identify bottlenecks across the Machine Learning (ML) stack and continuously improve system performance.

- Work closely with Artificial Intelligence (AI) engineers researchers and product teams to turn evolving model requirements into production-ready infrastructure.

Machine Learning Platform Engineer Outcomes

- AI infrastructure reliably supports production workloads at scale.

- Models can be trained evaluated deployed and improved efficiently.

- Inference systems deliver strong latency throughput reliability and cost efficiency.

- Machine Learning (ML) pipelines are reproducible observable maintainable and robust.

- Model and infrastructure regressions are detected quickly and diagnosed efficiently.

- Common Machine Learning (ML) infrastructure capabilities become reusable platform primitives rather than being rebuilt for every AI product.

- The AI stack can evolve rapidly as new models architectures and inference techniques emerge.

Qualifications :

Machine Learning Platform Engineer Qualifications:

- Machine Learning (ML) and Artificial Intelligence (AI) experience are required.

- Strong software engineering fundamentals and experience building production systems.

- Experience building Machine Learning (ML) infrastructure platforms or production machine learning systems.

- Experience with model deployment inference evaluation or data pipelines.

- Strong understanding of distributed systems and system reliability.

- Ability to write clean maintainable production-quality code.

- Comfortable working in ambiguous fast-moving environments.

- Bias toward ownership experimentation and continuous improvement.

- Tech Stack:  Python PyTorch JAX LLM and ML serving infrastructure such as vLLM SGLang or TensorRT-LLM Cloud infrastructure Distributed systems Machine Learning (ML)/data pipelines and workflow orchestration GPU infrastructure and performance tooling and Vector databases and retrieval infrastructure.

Benefits include medical insurance Dental Vision Savings Plan Options PTO etc.

Keywords:  San Francisco CA Jobs AI Artificial Intelligence Cloud Infrastructure Data Pipelines Distributed Systems GPU Infrastructure JAX LLM Large Language Model Machine Learning Platform Engineer ML Machine Learning Python PyTorch SGLang TensorRT-LLM Vector Databases vLLM Workflow Orchestration Work From Home Remote California Recruiters IT Jobs California Recruiting

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Additional Information :

All your information will be kept confidential according to EEO guidelines.

Remote Work :

Yes

Employment Type :

Full-time