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Reinforcement Learning Engineer at mlabs | New York

mlabsNew York, New York, United States
On-site Full-time

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Experience Level

Mid to Senior

Qualifications

Requirements:Production Experience: Demonstrated success in deploying autonomous learning systems within production environments, directly managing capital, pricing, traffic, or resources. Educational Background: Relevant degree in Computer Science, Mathematics, or a related field. Technical Skills: Proficiency in reinforcement learning algorithms, Python, and machine learning frameworks such as TensorFlow or PyTorch. Analytical Mindset: Exceptional analytical skills with a strong understanding of financial markets. Communication Skills: Excellent communication abilities, capable of conveying complex concepts to both technical and non-technical stakeholders.

About the job

Reinforcement Learning Engineer

Join our innovative team at mlabs, a leading software development firm at the forefront of decentralized finance. We are dedicated to building the infrastructure for the world's largest crypto social networks and digital asset launchpads. Our mission-driven group of builders values speed, technical excellence, and exceptional talent.

We are currently looking for a Reinforcement Learning (RL) Engineer who will be responsible for the end-to-end development of an RL-driven trading agent. This role involves managing real capital to enhance trading volume and user engagement within a dynamic memecoin ecosystem. The ideal candidate is an expert capable of integrating advanced modeling techniques with live financial operations. You will play a pivotal role in transitioning existing heuristic-based systems to learning-based methodologies while adhering to strict risk management protocols in a global 24/7 market.

Key Responsibilities:

  • Autonomous Agent Development: Lead the design, delivery, and refinement of an RL-driven trading agent to boost ecosystem engagement.
  • Objective Function Design: Create reward functions and policies closely aligned with product objectives while implementing strict downside risk management.
  • Validation Frameworks: Develop comprehensive evaluation and validation frameworks, including simulations and offline analyses, to minimize dependence on live testing.
  • System Transition: Oversee the transition of existing heuristic-based systems to cutting-edge learning-based approaches safely.
  • Technical Leadership: Act as the sole RL expert within a compact, high-performing team, responsible for the entire lifecycle from data modeling and deployment to monitoring and risk management.

Interview Process:

  1. Recruiter / HR Call: Initial screening to discuss your professional background, risk management philosophy, and cultural fit.
  2. Technical Interview: In-depth assessment of RL architecture, simulation frameworks, and experience in live production.
  3. Final Interview: Strategic discussion with leadership focusing on alignment with our mission, role expectations, and long-term goals.

About mlabs

mlabs is a premier software development firm specializing in decentralized finance solutions. We are committed to creating robust infrastructures that support the largest crypto social networks and digital asset launchpads. Our team is driven by a shared mission to innovate and excel in a rapidly evolving industry, focusing on speed and technical prowess.

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