We are looking for a Senior AI engineer to join our team. We are interested in individuals with knowledge and experience in developing and evaluating different reinforcement learning (RL) architectures and algorithms, and in their applications in experimentation and causal inference.
You will have the unique opportunity of defining and building from scratch reinforcement learning features for our next-generation machine learning platform for equitable fin-tech.
Working on the reinforcement learning algorithms that will run in our platform : definition, initial implementation, evaluation and deployment
Formulate real-world causal inference and experimental design problems in terms of different RL algorithms, and independently conduct research to decide upon the best approach.
or equivalent technical proficiency
Experience in reinforcement learning and its libraries (Keras-rl, TF-agents, garage, Pyqlearning, ChainerRL )
Solid coding skills in at least one of the following languages : Go, Scala, Python
RNS Solutions offers an outstanding culture that focuses on learning opportunities, international exposure by participation at international and national conferences, and career growth.
Marketing competitive salary
Health and maternity coverage
Sumptuous, home-cooked lunch (Free)
Accommodation for outstation employees (subsidized)
Expert-led fitness training (subsidized)
Performance bonuses and annual Increments
Chances to travel abroad
Mentoring and grooming
3rd Floor, Al-Rahim Arcade, National Market, Satellite Town, Rawalpindi, Pakistan
531 A Upper Cross Street #04-95, Hong Lim Complex, Singapore. Location
Hanyang Building 59-1 Gangnam-daero 6-gil, Seocho-gu, Seoul (Yangjae-dong) Location
Saudi Arabia Office
7198 Uthman Ibn Affan Rd, Al Nada, Riyadh 4415, Saudi Arabia
or equivalent technical proficiency Experience in reinforcement learning and its libraries (Keras-rl, TF-agents, garage, Pyqlearning, ChainerRL ) Solid coding skills in at least one of the following languages : Go, Scala, Python Preferred Qualification Knowledge of RL applications in FinTech, stocks and time series data analysis! Experience using a variety of RL algorithms : actor-critic, policy gradient, DQN, VFA, SARSA, Q-learning, model-based and model-free Monte Carlo, dynamic programming.
g. MLflow) Experience with continuous deployment of models with build pipeline Experience with databricks Experience with Spark performance tuning, data pipeline testing and MLlib