CoreLogic - Dallas, TX

posted 4 months ago

Full-time - Principal
Dallas, TX
1,001-5,000 employees
Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services

About the position

At CoreLogic, we are driven by a single mission—to make the property industry faster, smarter, and more people-centric. As a Principal Machine Learning Engineer, you will join a highly motivated hybrid-remote team tackling diverse AI projects ranging from traditional machine learning to cutting-edge imagery and large language models (LLM). This role emphasizes ownership of your work, continuous learning, and finding joy in what you do. You will support model training and prediction using various machine learning techniques on structured and unstructured data, including imagery and text. Your contributions will be vital in deploying large data and models using batch and API methods, as well as supporting multiple modalities such as spatial, 3D, and audio. You will perform your work in a cloud-based Linux environment, preparing and maintaining programs and documentation for software. Conducting defined quantitative and qualitative research projects independently, you will communicate research results to both internal and external stakeholders. The position requires a high degree of independence, as you will receive general direction and be competent to perform nearly all aspects of the job independently. You will also take a team leadership role in developing and refining an analytics development platform, mentoring and training junior colleagues along the way. CoreLogic is committed to cultivating a diverse and inclusive work culture that inspires innovation and bold thinking. We know our people are our greatest asset, and we encourage collaboration, valuing contributions, and developing skills that directly impact the real estate economy. By putting clients first and continuously innovating, we are working together to set the pace for unlocking new possibilities that better serve the property industry.

Responsibilities

  • Support model training and prediction using various types of machine learning techniques on structured/unstructured data, including imagery and text.
  • Support deployment of large data.
  • Support deployment of models using batch and API methods.
  • Support multiple modalities such as spatial, 3D and audio.
  • Perform work in a cloud-based Linux environment.
  • Prepare and maintain programs and documentation for software.
  • Conduct defined quantitative and qualitative research projects independently and communicate research results to internal and external stakeholders.
  • Take a team leadership role in developing and refining an analytics development platform.
  • Mentor and train junior colleagues.

Requirements

  • Bachelor's Degree or higher in Computer Science, machine learning, science, math, statistics, engineering field, or equivalent work experience.
  • 5+ years of HPC and/or MLOPS experience.
  • Experience in high performance computing HPC - e.g. BLAS, SIMD.
  • Experience in distributed computing - ray, spark, beam, Hadoop, AWS Batch, kubernetes.
  • Experience using python and/or C/C++.
  • Experience working in a cloud-based Linux environment.
  • Experience processing very large datasets.
  • Experience with pytorch, jax, Scikit-learn, mlflow, huggingface a plus.
  • Experience deploying Deep Learning models, e.g. Transformers, LLM, VLM, vision transformers, transfer learning, LORA, PEFT, CNN, or NLP a plus.
  • Experience using distributed training, e.g. DDP, FSDP, deepspeed a plus.
  • Strong problem solving and analytical ability.
  • Strong communication skills.
  • Ability to quickly and efficiently adapt to new concepts.
  • Ability to thrive in a team environment.
  • Strong working knowledge of multiple analytic development tools and programming languages.

Nice-to-haves

  • Publications or open source contributions a plus.
  • Real-time API processing, e.g. torchserve, bentoML a plus.
  • Experience in multiple modalities, such as GIS/spatial, 3D and audio a plus.

Benefits

  • Competitive salary and benefits package.
  • Diversity and inclusion initiatives.
  • Professional growth opportunities.
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