Senior Machine Learning Engineer

Key ResponsibilitiesLead the entire ML lifecycle from data collection and analysis to model deployment, monitoring, and optimizationApply deep learning and NLP techniques to develop solutions, potentially enhancing systems like search or recommendation enginesDesign and implement end-to-end ML pipelines, incorporating MLOps best practices for CI/CD, containerization (Docker, Kubernetes), and cloud deployment (AWS, GCP, Azure)Utilize LLM knowledge, including prompt engineering and fine-tuning, to build advanced generative AI applications and conversational AI solutionsPerform comprehensive data analytics, including statistical analysis and feature engineering, to inform model development and extract actionable insights from large datasetsWrite production-quality, robust code in Python (and potentially other languages like Java or Scala), ensuring code quality through reviews and testingCollaborate with cross-functional teams, including data scientists, data engineers, and product managers, to translate business requirements into technical ML solutionsRequirementsRequired Skills and QualificationsProven experience as a Machine Learning Engineer with a strong portfolio of deployed production modelsProficiency in Python and relevant ML frameworks/libraries (e.g., TensorFlow, PyTorch, scikit-learn)Expertise in data science methodologies, statistical analysis, and data analyticsHands-on experience with MLOps tools and practices for managing the ML application lifecycleStrong understanding of NLP and experience with LLMs and prompt engineering techniquesSolid software engineering background with knowledge of data structures, algorithms, and system designExcellent problem-solving, communication, and collaboration skills