Machine Learning Platform Engineer, Machine Learning (ML) and Artificial Intelligence (AI) Required, Work From Home at Parallel Partners in San Francisco, CA, United States

Job description

• 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.

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.

Requirements

• - 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.

Skills

Required

• Strong software engineering fundamentals
• Experience building production systems

Benefits

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