Engineer, Machine Learning Engineer

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Job Overview
The Machine Learning (ML) Engineer plays a pivotal role in advancing AI capabilities, focusing on the design, development, and deployment of machine learning models with an emphasis on large language models (LLMs) and state-of-the-art technologies. This position is essential for building scalable AI applications that deliver real-world impact, ensuring models are optimized for performance, reliability, and responsible use. Collaborating with various technical teams, they facilitate the seamless integration of LLM-powered applications into products and workflows. Their expertise ensures the organization remains at the forefront of AI innovation, reinforcing a culture of continuous improvement and leadership in applying advanced AI technologies.

Job Responsibilities:

• Build and maintain the entire machine learning lifecycle (research, design, experimentation, development, deployment, monitoring, and maintenance).  

• Assemble large, complex data sets that meet functional/ non-functional business requirements for machine learning.  

• Collaborate with data science, tech, and product teams on defining, architecting, and building data ingestion systems and model training pipelines from experimentation to deployment, monitoring, and continuous performance improvement.  

• Design, develop, and deploy machine learning and large language models (LLMs) to power scalable AI applications. 

• Fine-tune, optimize, and maintain AI models to ensure performance, reliability, and responsible use. 

• Collaborate with cross-functional technical teams to integrate AI-driven solutions into products, platforms, and workflows. 

• Conduct rigorous evaluations and benchmarking of AI models and applications to validate accuracy, efficiency, and trustworthiness. 

• Research and apply emerging machine learning techniques and AI frameworks to advance innovation and maintain industry leadership. 

• Build and maintain pipelines, tooling, and infrastructure for model training, deployment, and monitoring in production environments. 

• Ensure scalability, security, and compliance of AI systems while aligning with business and operational requirements. 

• Participate in other duties or projects as assigned by business management as needed. 

Education:

• Bachelor's Degree Computer Science, Data Science, Statistics, Informatics, Information Systems, Machine Learning, or another quantitative field (Required)  

• Master's/Advanced Degree Computer Science, Data Science, Statistics, Informatics, Information Systems, Machine Learning, or another quantitative field (Preferred)  

 
Work Experience: 

• Data Engineering, Data Science (Required)  

• Experience designing, developing, and deploying machine learning models and large language models (LLMs) in production environments (Required) 

• Experience building and maintaining end-to-end ML pipelines including data ingestion, training, deployment, monitoring, and optimization (Required) 

• Experience applying MLOps practices and cloud platforms (AWS, GCP, or Azure) for scalable AI solutions