Role overview
LOCATION:
Chicago -
SECTOR:
IT
REFERENCE:
29257
*AI Engineer
Company Description:**
Our Proprietary trading client is looking for an AI Engineer to work on high-impact machine learning (ML) and artificial intelligence (AI) initiatives that are central to the business strategy.
Role Description:
In this role, you will develop essential infrastructure and tools that harness AI and ML technologies to boost productivity, optimize efficiency, and uncover innovative solutions to complex business and technology challenges. Working alongside advanced technology and seasoned trading teams, you'll have the chance to take on exciting projects while establishing yourself as a subject-matter expert in a pivotal and forward-thinking position.
Key Responsibilities:
- Collaborate with technologists, traders, quantitative researchers, and data scientists to identify high-impact opportunities for integrating AI and machine learning into technology and business use cases.
- Drive end-to-end development of AI infrastructure and AI-driven applications, from initial proof-of-concept to production deployment and ongoing maintenance.
- Provide technical leadership in selecting, integrating, and optimizing AI and ML frameworks, libraries, and tools across diverse hardware and software environments.
- Develop frameworks to enable scalable, reproducible research.
- Create and maintain feature pipelines, feature stores, and model stores.
- Implement automated systems for continuous training, validation, and monitoring of models, minimizing downtime and ensuring reliability. Proactively troubleshoot performance bottlenecks, conduct root-cause analyses, and implement solutions to optimize GPU or CPU resource usage.
Qualifications:
- Bachelor’s or advanced degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
- Experience working with machine learning and artificial intelligence technology.
- Strong understanding of core machine learning and artificial intelligence concepts.
- Demonstrated experience in building, validating, deploying, monitoring, and updating production ML and AI models.
- Hands-on experience with MLOps and AIOps infrastructure and tooling.
- Experience with ML frameworks such as TensorFlow, PyTorch, TensorRT, or ONNX.
- Experience with Large Language Models, including RAG and fine-tuning techniques.
- Familiarity with compute infrastructure necessary to support operating AI and ML technology.
- Excellent programming skills in Python.
- Proficient in problem-solving and analytical reasoning. Exceptional communication and collaboration skills.
Location : Chicago, New York, London
- Please note that we will not respond and share information with applicants that we deem unsuitable for the position.
Consultant Name:
Lee Reynoldson
Consultant Email:
What you'll work on
- Collaborate with technologists, traders, quantitative researchers, and data scientists to identify high-impact opportunities for integrating AI and machine learning into technology and business use cases.
- Drive end-to-end development of AI infrastructure and AI-driven applications, from initial proof-of-concept to production deployment and ongoing maintenance.
- Provide technical leadership in selecting, integrating, and optimizing AI and ML frameworks, libraries, and tools across diverse hardware and software environments.
- Develop frameworks to enable scalable, reproducible research.
- Create and maintain feature pipelines, feature stores, and model stores.
- Implement automated systems for continuous training, validation, and monitoring of models, minimizing downtime and ensuring reliability. Proactively troubleshoot performance bottlenecks, conduct root-cause analyses, and implement solutions to optimize GPU or CPU resource usage.
What we're looking for
- Bachelor’s or advanced degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
- Experience working with machine learning and artificial intelligence technology.
- Strong understanding of core machine learning and artificial intelligence concepts.
- Demonstrated experience in building, validating, deploying, monitoring, and updating production ML and AI models.
- Hands-on experience with MLOps and AIOps infrastructure and tooling.
- Experience with ML frameworks such as TensorFlow, PyTorch, TensorRT, or ONNX.
- Experience with Large Language Models, including RAG and fine-tuning techniques.
- Familiarity with compute infrastructure necessary to support operating AI and ML technology.
- Excellent programming skills in Python.
- Proficient in problem-solving and analytical reasoning. Exceptional communication and collaboration skills.
Tags & focus areas
Used for matching and alerts on DevFound Ai Ai Engineer Machine Learning Data Science