RCI-LON-131389-1 Machine Learning Engineer (Deep Learning) - Only W2

Duration: 12 Months Hybrid, T, W, TH onsite mandatory, any Exelon satellite in Chicago, Philadelphia, Washington D.C., Baltimore, Delaware, etc Work hours: FT - 9am - 5pm EST / 8am - 4pm EST Position Overview We are seeking a highly skilled Machine Learning Engineer with strong expertise in data modeling, algorithm development, and advanced ML/DL techniques. The role focuses on designing, training, and optimizing models across text, image, and audio domains — with less emphasis on IT infrastructure, and more on core model creation and experimentation. Key Responsibilities Machine Learning & Deep Learning • Design, build, and train ML/DL models using TensorFlow, PyTorch, and transformer architectures. • Apply advanced techniques in neural networks, computer vision, and generative AI (GenAI). • Work on object detection, segmentation, and tracking (e.g., UNet, YOLO, RCNN, SAM/SAM2). • Develop and fine-tune foundation models, multimodal models, and LLMs (e.g., Stable Diffusion, ControlNet, CLIP). • Optimize models for performance, accuracy, and scalability on GPU infrastructure (e.g., NVIDIA A100/H100). • Conduct experimentation, hyperparameter tuning, and error analysis to continuously improve models. • Collaborate with data scientists and product teams to align models with business and domain-specific use cases. Data Modeling & Research • Develop data pipelines and modeling strategies for structured/unstructured data. • Evaluate datasets for feature engineering, augmentation, and preprocessing to support ML models. • Research and implement state-of-the-art ML/DL algorithms for real-world applications. • Document modeling processes, findings, and improvements. Required Qualifications • Master’s degree in Computer Science, Statistics, Mathematics, Engineering, Physics, or related quantitative field. • 5+ years of experience in machine learning and deep learning model development. • Strong expertise in Python, TensorFlow, PyTorch, and Hugging Face frameworks. • Proven track record of developing and deploying high-performing ML/DL models. • Strong foundation in data modeling, statistics, and algorithm design. • Excellent problem-solving, analytical, and collaboration skills. Preferred Qualifications • PhD in a relevant quantitative discipline. • Hands-on experience with computer vision and multimodal AI. • Familiarity with GenAI and LLM fine-tuning. • Contributions to research publications or open-source AI projects.