> Markdown version of [/jobs/ext/188915-sr-ai-ml-engineer](https://www.wearedevelopers.com/jobs/ext/188915-sr-ai-ml-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr. AI / ML Engineer - **Company:** PENNYMAC - **Location:** Westlake Village, CA, United States - **Experience:** Expert - **Salary:** $110,000.0 - $170,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Amazon Web Services, Amazon Elastic Compute Cloud, Amazon S3, Computer Vision, JIRA, BigQuery, Cloud Computing, Cloud Engineering, Cloud Storage, Code Review, Computer Programming, Continuous Delivery, Data Transformation, Dataspaces, Cursor (Graphical User Interface Elements), DevOps, Distributed Systems, Python (Programming Language), Machine Learning, Natural Language Processing, Scrum Methodology, Tensorflow, Software Engineering, Management of Software Versions, AI Infrastructure, Google Cloud, Feature Engineering, Data Ingestion, Pytorch, Large Language Models, Model Validation, Backend, Information Technology, Machine Learning Operations, Functional Programming, Spacy, Data Pipelines - **Published:** May 19, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=339bfe8490029591 ## About the Role We're looking for a highly experienced and motivated Senior AI Engineer to develop and deploy cutting-edge AI/ML solutions within our AI Accelerator Team. You'll work with and mentor a team of engineers responsible for leveraging the latest AI ( Artificial Intelligence ) technologies and ML ( Machine Learning ) models to deploy best-in-class tools for Pennymac's employees and customers. This role requires a deep understanding of AI agentic programming, machine learning algorithms, natural language processing (NLP), computer vision, AWS and GCP cloud technologies, and MLOps practices. Strong communication skills are essential to effectively collaborate within the team and provide technical mentorship to peers., * Bachelor's degree in Computer Science, Engineering, or a related quantitative field. * 5+ years of experience in a Platform Engineering or high-scale Backend role, with a focus on building resilient, distributed systems. * 3+ years of hands-on experience developing with Large Language Models (LLMs) and designing sophisticated agentic workflows. * Extensive experience navigating both Amazon Web Services (AWS) and Google Cloud Platform (GCP), specifically their respective AI and data ecosystems. * Deep proficiency in Python and its scientific stack (e.g., PyTorch, TensorFlow, spaCy) for developing high-performance machine learning applications. * Must have experience with AI Coding Assistants, specifically Cursor, Copilot or Devin, this is a core requirement for every member of our technical team who writes code. * Exceptional troubleshooting skills with a track record of identifying and resolving bottlenecks in complex AI infrastructure. * Proven ability to mentor engineering peers, fostering a culture of technical excellence and continuous growth. * Strong communication and collaboration skills Preferred Skills * FinTech or Mortgage Domain knowledge. * Experience in Evaluation Driven Development. * Experience in Agile/SCRUM using Jira. * Experience with feature flagging and service/API semantic versioning. * Experience building and maintaining effective relationships with product managers, architects, technical leads, and business stakeholders. ## Description Design and implement AI/ML solutions on AWS Bedrock and Google Vertex AI, including model selection, training, optimization, and deployment. * Utilize AWS services (e.g., EC2, S3, Lambda, SageMaker) and GCP services (e.g., Compute Engine, Cloud Storage, BigQuery, Vertex AI) to build and manage scalable cloud infrastructure for AI/ML workloads. * Develop and optimize high-performance machine learning models using Python and relevant libraries such as TensorFlow, PyTorch, and spaCy for predictive analytics and NLP. * Implement and manage MLOps practices to ensure efficient model development, deployment, monitoring, and retraining within the IDP pipeline. * Demonstrate proficiency in utilizing AWS Bedrock services (e.g., Titan FMs, foundation models) and Google Vertex AI services (e.g., Vertex AI Workbench, pre-trained APIs). * Design and implement robust data pipelines for efficient data ingestion, preprocessing, and feature engineering. * Identify and resolve performance and scalability issues in models and infrastructure to improve the accuracy and efficiency of tools in production. * Collaborate with cross-functional teams (e.g., product management, data science, software engineering) to deliver impactful solutions that meet business requirements. * Participate in code reviews and provide technical guidance to peers on best practices and latest technology trends. * Work with DevOps teams to ensure continuous delivery of the product using agile methodology. * Stay abreast of the latest advancements in AI/ML, NLP, computer vision, and cloud technologies to evaluate new techniques that enhance our AI solutions. * Utilize coding assistants such as Cursor, Copilot in the day to day development of products ## Related Videos - [Agentic employees in world's most downloaded FinTech app](https://www.wearedevelopers.com/videos/100123-agentic-employees-in-world-s-most-downloaded-fintech-app) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Improving quality with Agentic AI with Rovo Dev and Xray](https://www.wearedevelopers.com/videos/2005-improving-quality-with-agentic-ai-with-rovo-dev-and-xray) - [Pioneering AI Assistants in Banking](https://www.wearedevelopers.com/videos/1627-pioneering-ai-assistants-in-banking) - [DevOps Maturity Check – a way to balance autonomy and alignment](https://www.wearedevelopers.com/videos/58-devops-maturity-check-a-way-to-balance-autonomy-and-alignment) - [Collaboration Quantified: Lessons from Open Source Developer Networks](https://www.wearedevelopers.com/videos/1422-collaboration-quantified-lessons-from-open-source-developer-networks) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it)