Machine Learning Engineer

Our team is hiring a hands-on Reinforcement Learning (RL) professional with proven experience in designing, implementing, and optimizing RL solutions in real-world applications. This is an opportunity to make a direct impact by improving existing RL-powered products and expanding into new domains. Key Responsibilities: • Enhance and optimize current RL-based products through hands-on experimentation and iteration. • Lead or support exploratory projects to expand RL use into additional verticals. • Build, train, and deploy RL models on platforms such as SageMaker or comparable production environments. • Collaborate with data scientists, engineers, and product teams to align RL solutions with business goals. • Document decision-making, model choices, and reward shaping strategies for transparency and knowledge sharing. Minimum Qualifications: • Demonstrable, hands-on experience applying RL to solve real problems. • Practical familiarity with SageMaker or similar ML training/deployment environments. • Ability to clearly explain RL fundamentals: agents, environments, policies, rewards, and episodes. • Solid grasp of commonly used RL algorithms (e.g., DQN, PPO, A3C, etc.), including their strengths, weaknesses, and practical implications. • Experience working in multidisciplinary teams and excellent communication skills. Preferred Skills: • Deployment of RL solutions at scale in cloud or hybrid environments. • Experience with simulation environments for RL (e.g., OpenAI Gym, Unity ML-Agents, custom environments). • Prior experience integrating RL models with business processes or pipelines.