Machine Learning Engineer
GOOD FRIEND ELECTRICAL SUPPLIES, INC.
United States
about 2 months ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours
Job source
Tech stack
Artificial Intelligence
Algorithmic Trading
Big Data
Python (Programming Language)
Machine Learning
NumPy
Signal Processing
Data Streaming
Systems Integration
Deep Learning
Pandas
Information Technology
+1 more
Low Latency
Job description
- Founding Core AI & Quantitative Data Scientist (End-to-End) serving as a critical, high-impact technical pillar of the company’s research and production engines, reporting directly to the Founder.
- Driving full-lifecycle algorithmic development: leading deep academic and market research, formulating Proof of Concepts (PoC), training advanced predictive models, and deploying live production-grade trading strategies.
- Designing and optimizing high-throughput statistical architectures to process, analyze, and extract features from massive, high-velocity financial datasets and alternative data streams.
- Fine-tuning, backtesting, and validating complex models in live, volatile market environments to ensure absolute execution precision and low-latency response times.
- Core Domain & Ecosystem- Algorithmic Trading & Quantitative Finance, Time-Series Forecasting, Signal Processing, High-Velocity Big Data, Predictive Machine Learning, Deep Learning Architectures, Python Core, Rust Engineering, Financial Data Frameworks (Pandas, NumPy).
Requirements
- Academic Background: B.Sc. in a quantitative, scientific, or highly mathematical discipline (e.g., Computer Science, Data Science, Mathematics, Physics, Statistics, or Electrical Engineering) - Mandatory
- 5 years of proven professional experience dedicated to Machine Learning, Deep Learning, or Data Science within product-driven environments - Mandatory
- Recent, hands-on professional background specializing in Time-Series modeling, predictive sequence analysis, or signal processing - Mandatory
- Production-grade coding proficiency and architectural comfort in Python (specifically utilizing Pandas and NumPy) or Rust - Mandatory
- Prior experience handling high-volume, noisy, or unstructured time-series data streams - Mandatory
- Practical experience or strong technical affinity for quantitative environments, financial datasets, or low-latency system integration - Strong Advantage
- A highly autonomous, product-driven engineer with an entrepreneurial spirit, capable of moving seamlessly between abstract mathematical research and rigid production coding - Mandatory
About the company
An elite, boutique Quantitative Trading & Algo-Trading enterprise specializing in high-performance crypto-asset management and automated investment strategies.
The venture was established by highly prominent, industry-recognized pioneers with an outstanding track record in executive positions at the world’s most successful algorithmic trading firms.
Backed by extensive, multi-year institutional capital reserves ensuring long-term financial stability, the firm is currently expanding its core foundational engineering and research team.
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