Machine Learning Platform Engineer, Machine Learning, Artificial Intelligence

Job not on LinkedIn

🔥 1 hour ago

🌐 Mali, United States – Remote

🇲🇱 Mali – Remote 🇺🇸 United States – Remote

💵 $140k - $180k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🏗️ Platform Engineer

👻 Ghost score 0%

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Parallel Partners

WebsiteLinkedInAll Job Openings

1 - 10 employees

💳 Fintech

🤝 B2B

Fintech • B2B

Parallel Partners is a staffing firm specializing in the recruitment of information technology personnel for direct hire positions within the financial services and trading industries. Established in 1995 and headquartered in Chicago, they cater to clients such as international hedge funds, proprietary trading firms, investment banks, online brokerages, and trading software product vendors. Acquired by Next Step Systems in 2014, Parallel Partners focuses on placing high-frequency trading systems and algorithmic trading specialists, as well as providing expertise in financial engineering and risk management.

📋 Description

• 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 • 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 • Ensure AI infrastructure reliably supports production workloads at scale • Ensure models can be trained, evaluated, deployed, and improved efficiently • Ensure inference systems deliver strong latency, throughput, reliability, and cost efficiency • Ensure Machine Learning (ML) pipelines are reproducible, observable, maintainable, and robust • Detect and diagnose model and infrastructure regressions quickly • Create reusable Machine Learning (ML) infrastructure platform primitives • Enable the AI stack to evolve rapidly as new models, architectures, and inference techniques emerge

🎯 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 • Proficiency with Python, PyTorch, JAX, LLM and ML serving infrastructure such as vLLM, SGLang, or TensorRT-LLM, cloud infrastructure, distributed systems, ML/data pipelines and workflow orchestration, GPU infrastructure and performance tooling, and vector databases and retrieval infrastructure • Must be willing to take a 60 minute coding assessment

🏖️ Benefits

• Medical insurance • Dental insurance • Vision insurance • Savings Plan Options • PTO