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Machine Learning Engineer - Systematic Trading jobs in United States
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Acquire Me · 9 hours ago

Machine Learning Engineer - Systematic Trading

Acquire Me is a renowned quantitative trading firm specializing in deploying best-in-class programmatic models across global financial markets. They seek an ambitious ML Engineer to join their flagship research team, transforming quantitative research and trading while working closely with research teams to enhance proprietary workflows.
Staffing & Recruiting
Hiring Manager
Raj M.
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Responsibilities

Leverage the firm's cutting-edge platform to build scalable solutions that directly augment research capabilities and trading strategies
Optimize GPU utilization and training throughput to accelerate research and deployment for high-value ML teams
Contribute to core libraries for optimized data loading and resource scheduling, shaping the scalable AI platform

Qualification

PythonC++RustHPCDistributed training frameworksHardware resource managementML model serving infraPerformance profilingExceptional communication skills

Required

Strong coding experience in Python, C++, or Rust, and expertise in writing production-grade, optimized code for ML training/inference
Demonstrable interest in HPC and ML Infrastructure, staying current with GPU/TPU architecture, parallel processing (CUDA/RoCM), and low-latency networking (InfiniBand/NVLink)
Familiarity with distributed training frameworks (e.g., PyTorch Distributed, Horovod) and parallelism techniques (e.g., sharding, DeepSpeed)
Experience with hardware resource management and monitoring (e.g., Slurm, KubeFlow, Prometheus) for managing large GPU/CPU clusters
Exceptional communication skills for technical and non-technical collaboration, especially for ML infra/hardware translation

Preferred

Familiarity with ML model serving infra (e.g., Triton)
Low-level performance profiling (e.g., NVProf/NSight)
Custom kernel optimization

Company

Acquire Me

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We are a specialist technology recruiting firm dedicated to connecting the brightest and best STEM talent into the most exciting opportunities across the world’s most renowned scientific-led quantitative hedge funds, proprietary trading firms and high-growth start-ups.

Funding

Current Stage
Early Stage

Leadership Team

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Sanj Mahendran
Co-Founder
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Company data provided by crunchbase