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Temporary Machine Learning Finance Jobs (NOW HIRING)

IMC Inc

Machine Learning Engineer

Chicago, IL

$175K - $250K/yr

Machine Learning Engineer Chicago, United States; Hong Kong, Hong Kong; Sydney, Australia As a ... Since 1989, we've been a stabilizing force in financial markets, providing essential liquidity upon ...

The Nagler Group

Machine Learning Engineer

Manhattan, NY · On-site

Responsibilities : • Evaluating Generative AI systems for financial earnings call summarization ... Required : • Hands-on machine learning experience in production environments • Experience ...

IMC

Machine Learning Engineer

Chicago, IL · On-site

$175K - $250K/yr

As a Machine Learning Engineer, you will play a pivotal role in building systems that drive the ... Since 1989, we've been a stabilizing force in financial markets, providing essential liquidity upon ...

IMC

Machine Learning Engineer

Chicago, IL

$175K - $250K/yr

As a Machine Learning Engineer, you will play a pivotal role in building systems that drive the ... Since 1989, we've been a stabilizing force in financial markets, providing essential liquidity upon ...

Stefanini

Machine Learning Engineer

Allen Park, MI

Stefanini is looking for a Machine Learning Engineer(Allen Park, MI) For quick apply, please reach ... markets, including financial services, manufacturing, telecommunications, chemical services ...

Citadel

Machine Learning Engineer

Miami, FL

... financial markets. Your work will empower 100+ researchers to iterate faster on their agenda and ... Skills and Preferred Qualifications * 2+ years of experience in machine learning and software ...

Robinhood

Machine Learning Engineer

Bellevue, WA · On-site

... world's biggest financial problems. We're looking for bold thinkers. Sharp problem-solvers ... We're looking for an exceptional Machine Learning Engineer to help shape the future of our core ...

Stefanini Group

Machine Learning Engineer

Allen Park, MI · On-site

$61 - $66/hr

Stefanini is looking for a Machine Learning Engineer(Allen Park, MI) For quick apply, please reach ... markets, including financial services, manufacturing, telecommunications, chemical services ...

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How much do temporary machine learning finance jobs pay per year?

As of Jun 21, 2026, the average yearly pay for temporary machine learning finance in the United States is $92,631.00, according to ZipRecruiter salary data. Most workers in this role earn between $75,000.00 and $109,000.00 per year, depending on experience, location, and employer.
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Temporary Machine Learning Finance jobs near you

Machine Learning Engineer

IMC Inc

Chicago, IL

$175K - $250K/yr

Other

PTO

Posted 3 days ago

Job description

Machine Learning Engineer

Chicago, United States; Hong Kong, Hong Kong; Sydney, Australia

As a Machine Learning Engineer, you will play a pivotal role in building systems that drive the training and deployment of large-scale ML models across our global operations. You'll collaborate with leading researchers, hardware experts, and software engineers to build robust solutions that maximize the potential of GPU acceleration, distributed computing, and the latest open-source tools. Your work will influence our trading strategies by accelerating experimentation cycles that foster continuous innovation and refinement.

This is a unique opportunity to solve problems at the intersection of advanced machine learning and trading, where your contributions will shape the future of IMC's technology and trading capabilities.

Your Core Responsibilities:

  • Develop large-scale distributed training pipelines to manage datasets and complex models
  • Build and optimize low-latency inference pipelines, ensuring models deliver real-time predictions in production systems
  • Develop libraries to improve the performance of machine learning frameworks
  • Maximize performance in training and inference using GPU hardware and acceleration libraries
  • Design scalable model frameworks capable of handling high-volume trading data and delivering real-time, high-accuracy predictions
  • Collaborate with quantitative researchers to automate ML experiments, hyperparameter tuning, and model retraining
  • Partner with HPC specialists to optimize workflows, improve training speed, and reduce costs
  • Evaluate and roll out third-party tools to enhance model development, training, and inference capabilities
  • Dig into the internals of open-source ML tools to extend their capabilities and improve performance

Your Skills and Experience:

  • 5+ years of experience in machine learning with a focus on training or inference systems
  • Hands-on experience with real-time, low-latency ML pipelines in high-performance environments is a strong plus
  • Strong engineering skills, including Python, CUDA, or C++
  • Knowledge of machine learning frameworks such as PyTorch, TensorFlow, or JAX
  • Proficiency in GPU programming for training and inference acceleration (e.g., CuDNN, TensorRT)
  • Experience with distributed training for scaling ML workloads (e.g., Horovod, NCCL)
  • Exposure to cloud platforms and orchestration tools
  • A track record of contributing to open-source projects in machine learning, data science, or distributed systems is a plus

The Base Salary range for the role is included below. Base salary is only one component of total compensation; all full-time, permanent positions are eligible for a discretionary bonus and benefits, including paid leave and insurance. Please visit Benefits - US | IMC Trading for more comprehensive information.

Salary Range

$175,000 - $250,000 USD

About Us

IMC is a global trading firm powered by a cutting-edge research environment and a world-class technology backbone. Since 1989, we've been a stabilizing force in financial markets, providing essential liquidity upon which market participants depend. Across our offices in the US, Europe, Asia Pacific, and India, our talented quant researchers, engineers, traders, and business operations professionals are united by our uniquely collaborative, high-performance culture, and our commitment to giving back. From entering dynamic new markets to embracing disruptive technologies, and from developing an innovative research environment to diversifying our trading strategies, we dare to continuously innovate and collaborate to succeed.

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