Senior ML Platform Engineer – Data and Systems 5.5

Position Overview

We are looking for a Senior Machine Learning Engineer to join our team of passionate ML and software engineers. In this role, you will build the infrastructure, tools, and data pipelines that empower ML teams to deliver customer-facing features powered by Document Cloud data. You’ll work on high-impact projects combining system design, ML model evaluation, and data pipeline development, while ensuring our AI systems remain ethical, compliant, and scalable.

Key Responsibilities

• Build and maintain scalable AI data pipelines using Databricks, Spark, and cloud-native tools (e.g., Azure, AWS).
• Design and implement backend services and platform components powering ML and Generative AI features across products.
• Develop and evaluate ML models using classical and deep learning techniques, including GenAI, LLMs, SLMs, and Retrieval-Augmented Generation (RAG).
• Apply techniques such as model distillation and fine-tuning to optimize performance and efficiency of AI components.
• Leverage synthetic data generation and differential privacy to enhance products while preserving our commitment to ethical AI.
• Collaborate with product, legal, and policy teams to ensure regulatory compliance.
• Create reusable templates, frameworks, and documentation to accelerate ML development.
• Monitor and improve the efficiency, accuracy, and fairness of AI workflows in production.
• Mentor junior engineers and contribute to a culture of technical excellence and inclusion.

Required Qualifications

• Graduate degree (MS or Ph.D.) in Computer Science, Machine Learning, or a related field.
• 10+ years of experience in ML engineering or platform roles with scalable platforms (e.g., Databricks, Snowflake).
• Strong software engineering skills, including CI/CD, version control, and code reviews.
• Expert level proficiency in Python and ML frameworks.
• Experience deploying ML models in production environments and managing MLOps workflows.
• Familiarity with cloud platforms (Azure preferred) and Databricks.
• Strong understanding of data structures, algorithms, and system design.
• Excellent communication skills and a collaborative mentality.

Preferred Qualifications

• Experience with document intelligence, OCR, or NLP on unstructured data.
• Knowledge of vector databases and modern NLP techniques.
• Contributions to internal wikis, open-source ML tools, or platform documentation.

Benefits & Perks

• Compensation: U.S. pay range is $190,200–$345,650 annually. In California, the range is $238,700–$345,650. Pay varies based on location, experience, and role-specific factors.
• Eligibility for long-term incentives, including equity awards (non-sales roles follow the Annual Incentive Plan).
• A dynamic work environment with internal growth opportunities, continuous learning, and career mobility.
• Comprehensive policies ensuring equal employment opportunities and accommodations as needed.