Yardi is currently seeking a Machine Learning Engineer I (MLE1) to join our team, focusing on the end-to-end development of predictive models with an emphasis on Natural Language Processing (NLP) and Natural Language Understanding (NLU). As an MLE1, you will utilize tools like PyTorch, spaCy, and Pandas to build and optimize models within a production environment, enhancing our property management products. Your role will involve automating processes, improving productivity, and increasing customer satisfaction through advanced ML techniques. Key responsibilities include data handling, model development, statistical analysis, and system optimization for peak performance. What You’ll Do Develop and refine state-of-the-art Transformer based architectures and generative text models Research and implement solutions using large language models (LLMs) like Llama2 and GPT-3.5 Manipulate and reshape extensive data sets for effective training Collaborate with cross-functional teams to ensure the seamless integration of models Integrate machine learning solutions with databases, including SQL Server and Redis, to ensure efficient data storage and retrieval Analyze and document reasons for test failure; revise and debug assigned programs and procedures as necessary Efficiently identify and resolve issues that arise during the design, testing, and maintenance processes using problem-solving skills Use corporate approved source control applications (e.g., Microsoft Team Foundation Server, Git) to maintain code changes Use CRM systems to track cases, defects, and resolutions Adhere to department policies, procedures, and standards in the development and implementation of software Who You Are Bachelor’s degree in computer engineering, computer science, or similar field; or an equivalent combination of education and experience One plus (1+) years of experience as a machine learning engineer using Python or equivalent programming tools in an application development environment Proven track record of working on NLP, NLU, and OCR projects Experience in or knowledge of one or more of the following ML algorithms: Linear Regressions, Decision Tree, Logistic Regression, Random Forest, Support Vector Machines, Naïve Bayes, KNN Classification, K Means Clustering Experience in or knowledge of one more of the following libraries: TensorFlow, NumPy, Keras, SciPy, Pandas Strong proficiency in utilizing tools and libraries like Pytesseract, OpenCV, Flask, Streamlit, Seaborn, Pandas, and scikit-learn Solid knowledge of relationship databases (SQL Server) Proficiency in programming languages such as Python, with the ability to write clean, efficient, and maintainable code Excellent attention to detail with a high level of accuracy Independent problem-solving and analysis skills Clear, effective oral and written communication skills Demonstrated ability to meet critical deadlines and prioritize multiple tasks in a fast-paced environment Real Estate Runs On Yardi. About Us Yardi pioneers the property tech industry by seamlessly blending 40 years of tradition with forward-thinking innovation. We’ve created a team of over 9,000 employees in over 40 locations around the globe dedicated to making great real estate software products. Discover The Yardi Difference Yardi is more than just a software company – we are dedicated to creating a positive impact in our communities. Annually, Yardi extends philanthropic support to organizations chosen by our employees. Our team has contributed to over 350 nonprofits globally, demonstrating our commitment to various causes and communities. Our award-winning culture, consistently recognized by Glassdoor's prestigious "Best Place to Work", fosters support, collaboration, and growth. We prioritize your well-being with comprehensive benefits, including 100% paid employee medical premiums, company profit-sharing plan, and flexible work arrangements. Join Yardi and be part of a company that empowers, inspires, and celebrates success. #YardiCulture #BestPlaceToWork #YardiCareers Annual compensation $120,000 This position is not eligible for sponsorship. All submissions for open positions should be received through Yardi’s applicant portal, accessed from Yardi’s corporate website. EOE/Race/Gender/Disability/Vets #J-18808-Ljbffr