Remote Financial Trading Specialist Victoria

Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L.

Turing is looking for Trading professionals to work with our researchers to improve the performance of AI models. You will apply your expertise in trade execution, market analysis, order flow dynamics, and risk management to evaluate and train AI systems. If you enjoy solving complex problems in trading and are interested in shaping the future of AI in finance, please apply.

No prior AI experience is required.

• Evaluate LLM models on trading topics such as execution strategies, market microstructure, order book analysis, and position management.
• Create rubrics to assess model capabilities on tasks like trade sizing, risk/reward evaluation, technical analysis, and market impact assessment.
• Collaborate with AI researchers and fellow finance experts to shape training methods, evaluation strategies, and benchmarks.

• 2+ years of experience in Trading (e.g., equities, fixed income, FX, commodities, or derivatives trading at a bank, hedge fund, or prop trading firm).
• Robust grasp of market dynamics, execution algorithms, risk management, and trading strategies across asset classes.
• Excellent English written communication.

• CFA (Level I/II/III), FRM, Series 7/63, or MBA in Finance.

• Work on the cutting edge of AI and finance.
• Fully remote and adaptable work environment.
• Competitive hourly compensation of ~$100+/hour depending on experience.

• Commitment:
  Flexible, 10–30 hrs/week.
• Duration: ~1 month, with the possibility of extension based on performance and project needs.