RL Developers

Role & responsibilities :

• AI/ML Development:
• Design, develop, and deploy AI/ML models using Python and frameworks like TensorFlow, PyTorch, or Scikit-learn.
• Create robust reinforcement learning algorithms tailored to solve complex problems in the financial domain.
• Financial Analytics and Modeling:
• Implement predictive analytics models for market trends, risk assessment, portfolio optimization, and other financial applications.
• Work with financial datasets, ensuring data integrity and applying advanced analytics techniques.
• Collaboration and Integration:
• Collaborate with financial analysts, data scientists, and engineering teams to translate business requirements into scalable AI/ML solutions.
• Integrate machine learning models with existing financial systems and platforms.
• Performance and Optimization:
• Optimize models for performance, accuracy, and scalability in high-stakes environments.
• Conduct A/B testing and fine-tuning for deployed models.
• Research and Innovation:
• Stay updated with the latest advancements in AI/ML and financial technologies.
• Explore and prototype innovative solutions using state-of-the-art reinforcement learning techniques.

Preferred candidate profile

• Education:
• Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, or related fields.
• Technical Skills:
• Proficient in Python and its AI/ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn, NumPy, Pandas).
• Strong expertise in reinforcement learning and associated tools (e.g., OpenAI Gym, Ray RLlib).
• Solid understanding of financial systems, instruments, and domain-specific challenges.
• Experience with big data tools and platforms (e.g., Spark, Hadoop) is a plus.
• Soft Skills:
• Strong analytical and problem-solving skills.
• Ability to communicate complex technical ideas effectively to non-technical stakeholders.
• Proactive and detail-oriented with a focus on delivering high-quality solutions.

Preferred Experience

• Hands-on experience with financial forecasting, algorithmic trading, or risk modeling.
• Familiarity with regulatory compliance standards in the financial industry.
• Exposure to cloud platforms (AWS, Azure, Google Cloud) for deploying AI/ML solutions.