Company Introduction
NetByte.AI, LLC is a fintech-driven artificial intelligence and financial technology firm specializing in machine learning, quantitative intelligence, and data-driven financial solutions. Headquartered in Los Angeles with a growing global footprint, NetByte.AI partners with financial institutions, asset managers, fintech platforms, and digital asset firms to deliver advanced AI capabilities that enhance decision-making, optimize trading strategies, and power next-generation financial infrastructure. By combining deep expertise in financial markets with cutting-edge machine learning, data engineering, and scalable computing architectures, NetByte.AI enables clients to unlock predictive insights, automate complex processes, and improve risk-adjusted performance across traditional and digital financial ecosystems. As a strategic technology partner, NetByte.AI delivers AI-powered analytics, algorithmic modeling, and intelligent systems that support trading, risk management, portfolio optimization, and market intelligence—driving efficiency, transparency, and innovation in global capital markets. As part of its continued expansion in the Americas, NetByte.AI is establishing Los Angeles as its global AI innovation and engineering hub—leading the development of machine learning platforms, research capabilities, and enterprise-grade AI solutions for financial markets. NetByte.AI envisions a future where artificial intelligence, financial expertise, and scalable technology converge to create more intelligent, adaptive, and efficient global financial systems.
Job Overview
The Vice President, Machine Learning will serve as a senior executive leader responsible for defining and executing NetByte.AI’s global machine learning, AI strategy, and advanced analytics capabilities. Reporting directly to the CEO and COO, this role will lead all aspects of AI development—including machine learning research, model development, data strategy, and AI platform architecture—ensuring alignment with the company’s fintech model and long-term growth objectives. The VP of Machine Learning will play a critical role in building scalable AI systems, enhancing product intelligence, strengthening technological differentiation, and supporting revenue growth across AI-driven financial solutions and strategic partnerships. The ideal candidate brings deep experience in machine learning, quantitative finance, or AI engineering, with a proven ability to build high-performance AI teams, deploy production-grade models, and scale AI capabilities in complex, data-intensive environments.
Key Responsibilities
- Machine Learning Leadership & AI Strategy: Lead and oversee NetByte.AI’s global machine learning and AI strategy, ensuring alignment with corporate vision, product roadmap, and growth objectives. Define and strengthen NetByte.AI’s positioning as a leader in AI-driven financial technology and quantitative intelligence. Establish scalable AI frameworks, model governance standards, and best practices across the organization. Ensure all AI initiatives align with performance, explainability, and regulatory considerations.
- AI Platform Development & Model Innovation: Design and oversee development of machine learning models for trading, forecasting, risk management, and market intelligence. Lead end-to-end ML lifecycle, including data sourcing, feature engineering, model training, validation, deployment, and monitoring. Drive innovation in areas such as predictive analytics, reinforcement learning, NLP, and algorithmic optimization. Partner with engineering teams to build scalable, secure, and production-ready AI platforms.
- Go-To-Market Enablement & Product Integration: Collaborate with Product, Strategy, and Commercial teams to embed AI capabilities into client-facing solutions. Translate complex machine learning outputs into actionable insights for institutional clients. Support go-to-market strategies by aligning AI capabilities with client needs and market demand. Enable differentiation through AI-driven product innovation and performance advantages.
- Data Strategy & Infrastructure: Define enterprise data strategy, including data acquisition, governance, and architecture. Ensure availability of high-quality, real-time, and historical data for model development. Oversee data pipelines, cloud infrastructure, and scalable computing environments. Implement data security, privacy, and compliance standards across all systems.
- Research, Innovation & Thought Leadership: Position NetByte.AI as a leader in applied AI for financial markets. Oversee research initiatives, publications, and intellectual property development. Drive innovation through experimentation, prototyping, and collaboration with academic and industry partners. Represent NetByte.AI in AI, fintech, and quantitative finance forums and conferences.
- Data-Driven Performance & Optimization: Establish KPIs and performance benchmarks for model accuracy, efficiency, and business impact. Continuously monitor and optimize model performance in live environments. Implement feedback loops and model retraining processes. Align AI investments with revenue growth, product value, and strategic outcomes.
- Leadership & Organizational Development: Build, mentor, and lead a high-performing global AI and machine learning team. Foster collaboration between AI, engineering, product, and business teams. Develop technical leadership, talent pipelines, and succession planning. Promote a culture of innovation, rigor, accountability, and continuous learning.
Qualifications
- 20+ years of progressive experience in machine learning, AI engineering, quantitative finance, or data science leadership roles.
- Proven success in building and scaling AI/ML systems in fintech, financial services, or data-intensive industries.
- Strong understanding of financial markets, trading systems, risk models, and quantitative methodologies.
- Experience deploying production-grade machine learning systems at scale.
- Deep expertise in Python, ML frameworks (e.g., TensorFlow, PyTorch), and data infrastructure.
- Exceptional leadership, communication, and cross-functional collaboration skills.
- Master’s or PhD in Computer Science, Machine Learning, Mathematics, Engineering, or related field preferred.
Core Competencies
- AI Strategy & Execution: Translates advanced AI capabilities into scalable business solutions.
- Quantitative & Technical Expertise: Deep understanding of machine learning, data science, and financial modeling.
- Innovation Leadership: Drives cutting-edge research and applied AI development.
- Data & Systems Thinking: Builds robust, scalable, and efficient data ecosystems.
- Performance Optimization: Focuses on measurable model impact and continuous improvement.
- Leadership & Collaboration: Builds elite technical teams aligned with strategic objectives.