Sr. Machine Learning Engineer

We are Xome, a real estate services company headquartered in the Dallas, Texas area. As a subsidiary of Mr. Cooper Group, we employ over 1,200 team members nationwide. The nation’s largest financial services companies look to us for integrated and scalable business solutions that help simplify the mortgage and real estate process.

At the heart of everything we do is our purpose: To keep the dream of home ownership alive. If that sounds like a big, lofty goal, that’s because it really is. And we can’t do it alone. Our entire team is focused on helping create a stable and healthy housing industry. And, making sure the process of buying/selling a home doesn’t undermine the excitement of home ownership. That’s why we battle every day against the mediocrity of the status quo to simplify the complex world of mortgage servicing, lending and banking. We see ourselves as the experts who make doing business easier. While others bring complexity and a lack of transparency, we offer simplicity, trust, and visibility across the entire property lifecycle. And we deliver radical customer service.

Now, you might be wondering; how exactly do you pronounce Xome? Simple. ZOM (like home, if it started with a z)!

DUTIES:

Write efficient and robust queries to extract, modify and prepare the data for pre-processing from different structured, semi-structured, and unstructured datasets using SQL Servers, Databricks, Azure Data Factory and other cloud vendors. Train/Re-train a variety of Genetic Algorithm, Neural Network, Linear Regression, Gradient Boosting and other Supervised and Unsupervised ML models, using frameworks such as Tensorflow, PyTorch, Keras, and Sci-Kit Learn by building scalable programs and applications, debugging and deploying them. Conduct multivariate/univariate statistical analysis and feature distribution analysis on different domain specific datasets, to generate meaningful insights before being used in the ML models. Design, develop and implement MLOPs architecture, CI/CD pipelines, using MLFlow, Docker, asset bundles etc. Conduct literature review in the AVM/Real Estate domain and ML/AI domain of new publications, industry improvements, which contribute to the model/solution design process. Design, develop and implement Natural Language Processing (NLP) pipelines, that involve elements such as NER etc. Design, develop and implement Large Language Models (LLMs) and Gen AI solutions. Review ML models’ design, implementation, domain applicability of team members projects, and mentor junior data scientists on different ML models and workflows. Collaborate with Data Architecture, Data Engineering, Product, Marketing and other teams on strategizing ML/AI initiatives. Remote work permitted.

REQUIREMENTS:     

• Bachelor’s degree in Computer Science, Data Science or another related field of study and five (5) years of experience as a Machine Learning Engineer, Software Developer, or a related occupation.

Special Skills:      

• Also requires experience in the following:
•  ML tools like TensorFlow, PyTorch, Caffe, or Theano and have solved several real-life problems using these
•  Proficiency and experience in NLP like text processing, information retrieval, NER
• NLP, Vision, Classification, Extraction, Regression, Clustering, and Forecasting. 
•  Building deep learning models with TensorFlow/Keras or PyTorch. 
• Python and libraries for machine learning (such as scikit-learn, NumPy, Pandas, OpenCV) 
•  Data visualization, manipulation, versioning of big datasets
•  Feature Engineering
• Building the MLOps pipelines (using DataBricks, DVC, Kubeflow, Airflow, or Vertex AI, etc.).  
• Designing, building, and managing automation pipelines to operationalize the ML platform that should automate building Docker images, model training, and model deployment.
• Low-code and Auto ML libraries (for example, PyCaret and AutoKeras). 
• Azure technologies: Cloud Machine Learning, App Engine, Pub/Sub Streaming), Cloud Functions, Cloud Data Store and SQL
• Cloud-native development (Docker, Kubernetes, and DevOps) and the ability to select hardware to run an ML model within the expected latency. 
• AI products such as Azure Machine Learning, Amazon SageMaker, DataBricks, AutoML, etc.
• Writing code in programming languages such as Python or Java
• Design, build and work with RESTful Web Services in JSON and XML formats. 
• Version Control tools such as Git.
• Theoretical and practical knowledge of SQL / NoSQL databases with hands-on experience in at least one database system.
• Software development methodology such as Agile/Scrum

Xome is committed to nurturing a diverse and inclusive environment where every employee is empowered to be their authentic self.  We know that a large part of our success as a business is directly tied to our ongoing efforts to attract and retain diverse talent and maintain an inclusive environment where each employee can thrive.  Embracing and leveraging diversity through an inclusive work environment fosters new ideas, new insights, and constant innovation.  We strive to weave the principles of diversity and inclusion throughout the fabric of how we work, how we interact, and how we engage with our customers and the community.

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