Machine Learning Senior Engineer

ZS Associates - Thousand Oaks, CA

Full-time - Mid Level

Remote - Thousand Oaks, CA

10,001+ employees

Professional, Scientific, and Technical Services

About the position

The Machine Learning Senior Engineer at ZS is responsible for building and optimizing AI-enabled data products and solutions, particularly focusing on Large Language Models (LLMs). This role involves leading the development, fine-tuning, and deployment of machine learning models, ensuring they meet specific tasks such as text generation and conversational AI. The engineer will work collaboratively with client teams and global development teams to deliver impactful projects while adhering to best practices in coding and architecture.

Responsibilities

• Build, orchestrate, and monitor model pipelines including feature engineering, inferencing, and continuous model training.
• Lead the development, fine-tuning, and deployment of Large Language Models, ensuring optimization for specific tasks.
• Work with various Generative AI platforms to integrate LLMs into existing applications.
• Conduct thorough evaluations of LLMs using benchmarks and real-world data.
• Experiment with different model architectures and training techniques to improve performance.
• Scale machine learning algorithms to work on massive datasets and strict SLAs.
• Build and enhance ML Engineering platforms and components.
• Implement ML Ops including model KPI measurements and tracking.
• Write production-ready code that is easily testable and accounts for edge cases.
• Ensure the highest quality of deliverables by following architecture/design guidelines and coding best practices.
• Collaborate with client teams and global development teams to successfully deliver projects.
• Participate in scrum calls and effectively communicate work progress, issues, and dependencies.
• Contribute to researching and evaluating the latest architecture patterns and technologies.

Requirements

• Bachelor's/Master's degree in Computer Science, MIS, IT, or a related discipline.
• 2-4 years' experience in deploying and productionizing ML models.
• Demonstrated experience in developing, fine-tuning, and deploying Large Language Models.
• Hands-on experience with Generative AI platforms and proficiency in utilizing their APIs and SDKs.
• Experience in handling large datasets for training LLMs.
• Strong programming expertise in Python / PySpark.
• Experience in ML platforms like Dataiku, Sagemaker, or MLFlow.
• Experience in deploying models to cloud services like AWS, Azure, or GCP.
• Expertise in crafting ML Models for high performance and scalability.
• Experience in implementing feature engineering and real-time model predictions.
• Good fundamentals of machine learning and deep learning.

Nice-to-haves

• Experience with Spark or other distributed computing frameworks.
• Understanding of DevOps, CI/CD, and data security.
• Experience in data engineering in Big Data systems.

Benefits

• Comprehensive total rewards package including health and well-being benefits.
• Financial planning support.
• Annual leave and personal growth opportunities.
• Professional development programs and career progression options.
• Flexible working arrangements combining remote and on-site work.