Hybrid ML Engineer: LLMs, Spark & Data Pipelines

UNAVAILABLE; Dublin; Hybrid; EUR 90,000 - 130,000; Full time

Job summary

DocuSign is seeking an experienced Machine Learning Engineer to design, develop, and optimize large-scale data processing systems. The role focuses on distributed computing, data pipelines, and applied LLM integration to production applications.

As an individual contributor reporting to the ML Engineering Manager, you will build scalable pipelines with Python, Spark or Ray, and implement LLM-based solutions with robust data quality and monitoring. Hybrid in-office weekly.

Qualifications

• 5+ years of experience in data engineering or related roles.
• Experience with Python for data engineering and automation.
• Experience with distributed computing frameworks like Apache Spark or Ray.
• Experience integrating LLMs (e.g., OpenAI, Azure OpenAI, Anthropic, or similar) into applications via APIs, including prompt design, response parsing, and error handling.
• Experience with distributed systems concepts including data partitioning and sharding strategies, fault tolerance and replication, consistency models and distributed consensus, load balancing and resource management.
• Experience with distributed file systems (Azure Data Lake, S3, HDFS).
• Experience implementing REST APIs using Python frameworks such as FastAPI, Flask, or similar.
• Experience with containerization and orchestration (Docker, Kubernetes).
• Experience with SQL and database optimization techniques.
• Experience with data structures, algorithms, and software design patterns.
• Experience with version control systems (Git) and CI/CD pipelines.
• Bachelor's or Master's degree in Computer Science, Engineering, or related field, or equivalent practical experience.

Responsibilities

• Architect and maintain high-performance, fault-tolerant distributed systems to ensure scalability and availability.
• Design, build, and optimize scalable data pipelines and ETL processes using Python, Spark, and Ray to process complex, unstructured datasets.
• Develop batch data processing workflows to support analytics and machine learning initiatives.
• Integrate and operationalize Large Language Models (LLMs) such as OpenAI, Azure OpenAI, or similar platforms into production applications, including PII detection and redaction workflows.
• Design and maintain prompt engineering strategies, fine-tuning pipelines, and evaluation frameworks for LLM-based solutions.
• Optimize data processing jobs and system performance for cost-efficiency and reliability.
• Collaborate with applied scientists, SMEs, and engineering teams to understand data requirements and deliver robust solutions.
• Implement data quality frameworks and monitoring systems to ensure data integrity.
• Troubleshoot and resolve complex data processing issues in production environments.

Skills

Python

Distributed computing

Spark

Ray

LLMs integration

REST APIs

Docker

Kubernetes

SQL

Git/CI-CD

Data processing

Education

Bachelor's or Master's in CS/Engineering

Tools

Docker

Kubernetes

FastAPI/Flask

Azure Data Lake/S3/HDFS

Spark

Ray

Git

CI/CD

Job description

DocuSign is seeking an experienced Machine Learning Engineer to design, develop, and optimize large-scale data processing systems. The role focuses on distributed computing, data pipelines, and applied LLM integration to production applications.

As an individual contributor reporting to the ML Engineering Manager, you will build scalable pipelines with Python, Spark or Ray, and implement LLM-based solutions with robust data quality and monitoring. Hybrid in-office weekly.