Quick Summary
Key Responsibilities
Drive end-to-end development of AI infrastructure and AI driven applications: from initial proof-of-concept to production deployment and ongoing maintenance. Collaborate with technologists, traders,
Requirements Summary
Bachelor’s or advanced degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
Technical Tools
EngineeringData Science
Key Responsibilities:
- Drive end-to-end development of AI infrastructure and AI driven applications: from initial proof-of-concept to production deployment and ongoing maintenance.
- 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.
- Implement automated systems for continuous training, validation, and monitoring of models, minimizing downtime and ensuring reliability.
- Provide technical leadership in selecting, integrating, and optimizing AI and ML frameworks, libraries, and tools across diverse hardware and software environments.
- Create and maintain feature pipelines, feature stores, and model stores.
- Develop frameworks to enable scalable, reproducible research.
- 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.
- 3+ years of experience working with machine learning and artificial intelligence technology.
- Strong understanding of core machine learning and artificial intelligence concepts.
- Excellent programming skills in Python.
- Demonstrated experience in building, validating, deploying, monitoring, and updating production ML and AI models.
- Hands-on experience with MLOps and AIOps infrastructure and tooling.
- Proficient in problem-solving and analytical reasoning.
- Exceptional communication and collaboration skills.
- 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.
#LI-BL1
Listing Details
- Posted
- February 27, 2026
- First seen
- March 26, 2026
- Last seen
- April 14, 2026
Posting Health
- Days active
- 19
- Repost count
- 0
- Trust Level
- 39%
- Scored at
- April 14, 2026
Signal breakdown
freshnesssource trustcontent trustemployer trustcandidate experience
External application · ~5 min on Drweng's site
Please let Drweng know you found this job on Jobera.
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AI Engineer