Sr Machine Learning Engineer (Hybrid)

Who We AreJoin a team that puts its People First! As a member of First American's family of companies, Data & Analytics is a national provider of property-centric information, analytics, risk management and valuation solutions. First American maintains and curates the industry's largest property and ownership dataset with over 7 billion document images. Our major platforms and products include: DataTree®, FraudGuard®, RegsData™, TaxSource™ and ACI®. The First American Data & Analytics division boasts more than 20 patents and remains at the forefront of innovation - leveraging technology and data to deliver best-in-class decisioning solutions. Fueled by our industry-leading data and using our technology and proprietary process, our solutions provide lenders, real estate and title companies with actionable insights - enabling them to make better, increasingly automated, decisions. With offices in all major metropolitan areas, including California and New York, DNA teams work collaboratively from across the country. Since 1889, First American (NYSE: FAF) has held an unwavering belief in its people. They are passionate about what they do, and we are equally passionate about fostering an environment where all feel welcome, supported, and empowered to be innovative and reach their full potential. Our inclusive, people-first culture has earned our company numerous accolades, including being named to the Fortune 100 Best Companies to Work For® list for nine consecutive years. We have also earned awards as a best place to work for women, diversity and LGBTQ+ employees, and have been included on more than 50 regional best places to work lists. First American will always strive to be a great place to work, for all. For more information, please visit www.careers.firstam.com.What We DoResponsible for building and implementing deep learning-based transformer-based machine learning models in the areas of Natural Language processing (NLP) and Computer Vision (CV). Build and manage the infrastructure on cloud to deploy Machine Learning models in production in conformance with organization's security and compliance needs. Experience in fine tuning Large Language Models (LLM's) to task specific data sets. Deploy LLM and deep learning models in production and optimize real time inference on millions of predictions daily. This role can focus on R&D and/or Engineering responsibilities.
R&D Role: Responsible for ML Operations with expertise in fast serving inference, ML flow, research, and development (R&D), and a strong focus on best practices in ML development and operations. Develop and maintain robust and efficient ML infrastructure, ensuring smooth ML flow from development to production, drive innovative R&D initiatives, and implement industry-leading best practices. Monitor and address model drift to ensure model performance and accuracy over time. Drive R&D initiatives to explore and implement innovative ML operations techniques, deployment technologies, and monitoring frameworks. Ensure efficient data pipelines and data availability for ML model serving and monitoring.
Engineering Role: Build and manage the infrastructure on cloud (Azure or GCP or Databricks) to deploy Machine Learning models in production in conformance with organization's security and compliance needs. Experience in Infrastructure as Code (IaC) automation and a strong background in software engineering and machine learning, as well as experience building and maintaining large-scale machine learning models in production. Implement and maintain model monitoring tools and processes to track key metrics, generate alerts, and facilitate proactive model maintenance. Work closely with cross-functional teams to identify and address infrastructure bottlenecks, optimize resource allocation, and improve scalability of ML systems.

HOW YOU'LL CONTRIBUTE

• Design and architect LLM models based on the Transformer architecture for various NLP tasks.
• Implement and experiment with the Retrieval Augmented Generation (RAG) technique to enhance the generation capabilities of LLMs.
• Implement and maintain efficient ML flow processes, including model versioning, deployment, and monitoring to enable seamless transition from development to production.
• Develop and maintain vector databases to store and index semantic embeddings of textual data for efficient and scalable search.
• Implement and experiment with different fine-tuning techniques, such as transfer learning, regularization, and data augmentation. Fine-tune pre-trained LLMs on specific datasets to optimize performance for target applications.
• Develop and test novel LLM architectures, taking into consideration factors like model size, computational efficiency, and memory requirements.
• Optimize LLMs for deployment in resource-constrained environments through model quantization and compression techniques.
• Design and implement continuous integration/continuous delivery (CI/CD) pipelines for machine learning (ML) models, ensuring high availability and low latency.
• Build and maintain data pipelines that support ML models.
• Monitor model performance and quality in production and implement mechanisms to detect and prevent model drift.
• Collaborate with cross functional teams, including researchers and software engineers, to integrate LLMs, vector databases, and semantic search capabilities into production systems.
• Automate the deployment and scaling of ML models and ensure that they are secure and comply with relevant regulations.
• Stay up to date with the latest advancements in LLM research, vector database technologies, and semantic search techniques.
• Contribute to the company's knowledge base in NLP, LLMs, vector databases, and semantic search through documentation, research papers, and internal presentations.
• May act as a technical advisor to other teams, providing guidance on MLOps best practices and solutions.
• May design, implement and maintain IaC automation scripts, using tools such as Terraform, Ansible, or Puppet
• Other duties as assigned.
• Required to perform duties outside of normal work hours based on business needs.
• Other duties as assigned

WHAT YOU'LL BRING

Required Education, Experience, Certification/Licensure

• Bachelor's degree in computer science, software engineering, or a related field
• Master's or PhD degree preferred.
• 5-7 years of related work experience in building and maintaining large scale machine learning platform solutions

KNOWLEDGE, SKILLS, AND ABILITIES (KSAs)

• Strong knowledge of software engineering principles and experience with at least one programming language (e.g., Python, Java, Scala, etc.)
• Strong background in neural network architecture and ability to iterate on various parameters to provide high performant and accurate models. 
• Strong understanding of ML models and algorithms in the areas of Large Language Models
• Experience with cloud computing platforms, such as AWS, GCP, or Azure
• Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes)
• May require experience with IaC automation tools and scripts (e.g., Terraform, Ansible, Puppet, etc.)
• Experience with Snowflake and cloud-based data pipelines.
• MLaaS platforms such as Azure ML, AWS Sagemaker, and Databricks
• Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams.
• Proficient in version control and DevOps tools such as GitLab/GitHub/Azure DevOps
• Strong organizational or project management skills.
• Strong written and verbal communication skills.
• Constantly updating personal technical and business knowledge and skills and mentoring others to increase the knowledge and skills of the team.
• Solid presentation skills.

Pay Range: $126,100 - $168,100 Annually

This hiring range is a reasonable estimate of the base pay range for this position at the time of posting. Pay is based on a number of factors which may include job-related knowledge, skills, experience, business requirements and geographic location.

What We OfferBy choice, we don't simply accept individuality – we embrace it, we support it, and we thrive on it! Our People First Culture celebrates diversity, equity and inclusion not simply because it's the right thing to do, but also because it's the key to our success. We are proud to foster an authentic and inclusive workplace For All. You are free and encouraged to bring your entire, unique self to work. First American is an equal opportunity employer in every sense of the term.Based on eligibility, First American offers a comprehensive benefits package including medical, dental, vision, 401k, PTO/paid sick leave and other great benefits like an employee stock purchase plan.