RE Partners

Compensation

Full Description

Machine Learning Engineer Key Responsibilities Develop and maintain machine learning models for time-series forecasting, anomaly detection, and clustering in real-time environments. Integrate Large Language Models (LLMs) for task-specific use cases, including prompt optimization and caching strategies. Design and implement end-to-end MLOps pipelines on AWS, including model training, validation, deployment, and monitoring. Optimize models for edge and mobile execution with a focus on performance, battery, and resource constraints. Collaborate with data engineers to handle high-velocity streaming data pipelines. Evaluate and improve prompt quality, retrieval techniques, and contextual embeddings for LLM workflows. Ensure scalability, reliability, and real-time performance of deployed ML systems. Required Skills Strong Python skills, with experience in ML libraries such as scikit-learn, PyTorch, TensorFlow. Hands-on experience with real-time time-series data processing (e.g., Kafka, Flink, Spark Streaming). Proven experience in time-series modeling: LSTM, Prophet, Transformer-based architectures. Experience with unsupervised learning and clustering techniques (DBSCAN, K-Means). Familiarity with LLM APIs (OpenAI, Anthropic, Gemini) and prompt engineering best practices. Understanding of prompt caching and embedding-based retrieval techniques. Solid MLOps experience on AWS (SageMaker, Lambda, ECS, CloudWatch, Step Functions). Experience with model quantization, pruning, ONNX conversion, and other techniques for mobile deployment. Nice-to-Have Experience with vector databases (e.g., Pinecone, FAISS, Weaviate). Exposure to edge AI toolkits (e.g., TensorFlow Lite, Core ML, MediaPipe). Understanding of data privacy and security considerations in streaming ML applications. Join Our Global Team: We invite you to apply for the position at RE Partners. Join us in shaping the future of business technology consulting and transforming the way organizations thrive in a digital world. As a diverse, woman-owned global business, we pride ourselves on keeping talent happy – our 7% attrition rate speaks volumes. Bring your talented friends along and earn a referral bonus Equal Opportunity Employer: We are an equal opportunity employer and welcome applications from all qualified individuals regardless of race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, disability, or veteran status.