Senior Lead Machine Learning Engineer

Salary: $211000 - 289000 per year Requirements: We require a bachelors degree. We require at least 8 years of experience designing and building data-intensive solutions using distributed computing; internship experience does not count. We require at least 4 years of programming experience with Python, Scala, or Java. We require at least 3 years of experience building, scaling, and optimizing machine learning systems. We require at least 2 years of experience leading teams that develop machine learning solutions. We prefer a masters degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related discipline. We prefer 6+ years of experience designing, developing, delivering, and supporting AI services at scale. We prefer 3+ years of experience developing AI and machine learning algorithms or technologies using Python. We prefer 2+ years of experience with Retrieval Augmented Generation (RAG). We prefer experience keeping pace with the latest machine learning research and applying new techniques thoughtfully in production. We prefer experience deploying scalable AI and ML solutions in public cloud environments such as AWS Bedrock, Google Cloud, or Azure. We prefer experience designing, implementing, and scaling complex data pipelines for ML models and assessing their performance. Responsibilities: We lead dedicated pods of software, data, and machine learning engineers to build AI/ML capabilities for credit and financial risk management products, while mentoring the team on these core technologies. We design, build, and deliver AI-powered products and components that address real business challenges, applying expertise in model experimentation, LLM inference, similarity search, and agentic AI in partnership with Product and Data Science. We collaborate with engineers, data scientists, and designers to develop and scale AI-powered products that improve associate productivity and create outstanding customer value. We shape machine learning infrastructure decisions using our understanding of modeling approaches, including model selection, data and feature choice, training, hyperparameter tuning, dimensionality, bias/variance tradeoffs, and validation. We solve complex problems by writing and testing application code, developing and validating ML models, and automating testing and deployment. We retrain, maintain, and monitor production models. We use or build cloud-based architectures, technologies, and platforms to deliver optimized ML models at scale. We construct efficient data pipelines that supply ML models. We apply continuous integration and continuous delivery best practices, including test automation and monitoring, to support reliable deployment of ML models and application code. We ensure code is well controlled to reduce vulnerabilities, models are governed with a strong risk mindset, and our ML practices align with Responsible and Explainable AI standards. We work with a broad set of open-source and SaaS AI technologies and program in Python, Scala, or Java. Technologies: AI AWS Azure Cloud Support Java LLM Machine Learning Python Scala More: We are Aperture Cloud, and we are seeking a Senior Lead Machine Learning Engineer to join our Agile team focused on productionizing machine learning applications and systems at scale. In this role, we work across engineering, modeling, data, and product disciplines to deliver AI-powered solutions that drive business impact and customer value. We offer a comprehensive and competitive benefits package that supports overall well-being, along with performance-based incentive compensation that may include cash bonuses and long-term incentives. This position includes location-based salary ranges for Cambridge, McLean, New York, and Richmond, and candidates in other locations will be aligned to the applicable local pay range. We also support eligible applicants with employment authorization sponsorship and are committed to an inclusive, equal opportunity, drug-free workplace. last updated 28 week of 2026