Staff AI Engineer

🕒 Abril 7

🐊 Florida, New York, +1 estados a mais – Remoto

🐊 Florida – Remote 🗽 New York – Remote 🍂 Massachusetts – Remote

💵 $175.000 - $250.000 / ano

⏰ Tempo Integral

🔴 Especialista

🤖 Engenheiro de IA

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MLabs

SiteLinkedInTodas as Vagas

51 - 200 funcionários

A MLabs Consulting ajuda a configurar especificações de projetos, implementar, gerenciar e manter projetos técnicos para IA, Fintech, Tecnologia da Informação e mais. Somos especializados em programação funcional, compiladores, IA, DevOps e desenvolvimento full-stack.

Descrição

• Feedback Loop Implementation: Design and implement systems that connect trade outcomes back to strategy improvement, specifically focusing on signal selection, risk parameters, position sizing, and timing. • Evaluation Frameworks: Build frameworks to quantify which signals and market conditions accurately predict profitable trades versus noise. • Automated Strategy Generation: Develop systems to explore new configurations, backtest them against real fleet data, and surface candidates for deployment autonomously. • Market Adaptation: Build mechanisms to detect shifts in market conditions (e.g., trending vs. choppy) and adapt fleet behavior in real-time. • Fleet Monitoring: Create higher-order agents for automated monitoring to catch configuration errors and performance degradation across all concurrent agents. • Performance Attribution: Decompose trades into component drivers—signal accuracy, execution efficiency, and exit timing—to feed insights back into strategy design. • Coordination & Risk: Manage concentration risk and capital allocation across the fleet, balancing the exploration of new approaches with the exploitation of proven strategies. • Infrastructure Ownership: Transition from external LLM dependence to controlled intelligence, evaluating hosting strategies ranging from proxied external models to fine-tuned, domain-specific models. • Data Capture: Build the telemetry and data capture layer to ensure every decision and outcome is structured and queryable. • Domain-Specific Training: Determine the efficacy of domain-specific training over general-purpose prompting and build the necessary pipelines for implementation. • Inference Optimization: Optimize inference for many concurrent agents, ensuring structured decision outputs and cost-efficiency at scale.

🎯 Requisitos

• Production ML Engineering: Proven experience training, deploying, and maintaining models that run in production and directly impact business outcomes. • Reinforcement/Online Learning: Deep understanding of the practical challenges of learning from real-world outcomes rather than static datasets. • Closed-Loop Systems: A track record of building systems where predictions lead to actions that generate outcomes, which then feed back into improved predictions. • Software Engineering: Proficiency in Python is required, with additional comfort in Go or TypeScript for production services. Experience building data pipelines and distributed systems is essential. • Preferred Experience: Background in signal generation, alpha research, portfolio optimization, or execution. • LLM Specialization: Experience with fine-tuning and serving (PEFT/LoRA, vLLM, TGI) or custom inference pipelines. • Multi-Agent Systems: Experience designing environments where autonomous agents coordinate or learn from one another. • Domain Knowledge: Background in on-chain data, DeFi protocols, or sectors where agents make sequential decisions under uncertainty (e.g., robotics, game AI).

🏖️ Benefícios

• Base Salary: $175,000 – $250,000 USD (dependent on location and experience). • Equity: Approximately 1% initial stock grant, with significant valuation growth potential. • Performance Incentives: Eligibility for salary increases and bonuses tied directly to revenue and usage. • Token Participation: Pro-rata participation in the client’s planned 2026 token launch. • Ownership: High-impact role with meaningful upside tied directly to the success of the autonomous fleet.