Machine Learning Engineer
2 weeks ago
About the job Machine Learning Engineer
Protogon Research builds AI models with a deep understanding of the world, monetizing them through proprietary trading. Founded and led by serial entrepreneur Rafael Cosman, the co-founder of Archblock and the DeFi Protocol TrueFi, Protogon Research is building superintelligence.
We believe trading is a powerful testbed for developing highly intelligent AI systems, offering unique advantages over other approaches. Backed by top VCs, our highly technical team is on a mission to build the most transformative technology of the 21st century.
Why Build AI Trading Systems?
Focusing on trading provides several key advantages:
- Proprietary models and datasets - This helps us avoid the race to the bottom faced by many other AI companies.
- Fast innovation cycle - Technological advancements directly translate into increased revenue, allowing us to rapidly test and implement improvements.
- Pure focus on AI development - With no need for sales, marketing, or customer support, we can concentrate on building groundbreaking systems.
- True understanding, not imitation - We create AI that deeply understands the world rather than just replicating human behavior or generating superficially pleasing outputs.
We are a small, dynamic team of eight based in Redwood City, CA, and were seeking talented Machine Learning Engineers to help us build impactful technology and drive innovation. We believe working in person fosters the most fun, engaging, and creative work, so this role will be based at our Menlo Park office.
Responsibilities & Expectations:
- Designing Model Architectures: Core work on improving our model architecture and training, with a focus on achieving measurable gains in model accuracy and reducing training time
- Evaluating Model Performance: Working on the training framework to efficiently train and test models, and expanding how we characterize/measure our trained models
- Expanding Data Sources: Finding and integrating more novel data to increase model performance on backtest as well as real-world assessments
- Monitoring and Alerts: Designing monitoring systems to detect and alert the team to anomalies with live trading strategies, aiming to reduce detection and response time, minimize false positives, and improve system reliability.
- Experienced Machine Learning Engineer: Strong background in ML development with hands-on experience in both theoretical and practical applications. Proficient in deep learning frameworks such as PyTorch, TensorFlow, and Jax, with expertise in feature engineering, model optimization, and evaluating model performance. Minimum of 2 years of experience.
- AI/Financial Markets Enthusiast: Interested in AI, AGI, and financial markets.
- Discreet: Able to handle and protect proprietary technology and strategies with the highest level of confidentiality.
- Takes Ownership: Proactively takes responsibility, drives projects, and contributes effectively within a small, agile team.
- Experience in quantitative finance, trading systems, or market modeling
- Strong programming skills in Python
- Knowledge of high-performance computing (HPC) and distributed computing frameworks
- Experience with cloud platforms (AWS, GCP)
- Competitive Salary
- Comprehensive Benefits: Medical, Dental, and Vision coverage
- Additional Benefits: 401K, FSA, and HSA options
- Flexible Time Off: Vacation policy, sick days, and holidays
Note: We are open to candidates who are interested in an engineering lead role, involving some recruiting and management responsibilities in addition to significant coding work. Compensation will be based on the scope of responsibilities and level of experience.
At this time, we are unable to provide visa sponsorship. Candidates must have authorization to work in the United States without requiring sponsorship, now or in the future.
If you are excited to grow with us, push the boundaries of what is possible, and be a part of shaping the future of AI, we'd love to connect
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