Senior Applied Scientist

Docusign • Seattle, WA

2d • Hybrid

About The Position

We are seeking an experienced Applied Scientist to join our team. Our team, originally part of Lexion and recently acquired by Docusign, offers the unique combination of a fast-paced startup environment with the substantial resources and backing of Docusign. You will be instrumental in leveraging Lexion’s state-of-the-art AI to research, design, and deploy innovative features and products for Docusign’s extensive customer base. A core focus of this role will be the end-to-end design, implementation, and evaluation of machine learning pipelines, working in close partnership with engineering teams to successfully integrate these models into customer-facing functionality. This position is an individual contributor reporting to a Senior Manager, Machine Learning.

Requirements

• Masters’s or higher degree in a relevant field (computational linguistics or equivalent field with computational analysis)
• 6+ years experience in computational linguistics or language data processing
• Experience working in an agile software development environment
• Proficiency in modern programming languages for ML development, such as Python
• Experience with language annotation and other forms of data markup for ML systems
• Experience with programming and data analysis with languages and platforms such as Python or SQL
• Experience with prompt engineering
• Experience in bootstrapping language data collections in a quickly changing environment
• Experience designing and conducting data experiments.
• Experience with version control, unit tests, and other programming best practices
• Experience with MLOps practices, tools, and platforms (e.g., model versioning, serving, monitoring, and pipeline orchestration)
• Experience with cloud platforms for ML workloads (Azure, AWS, GCP)
• Experience using Git or other modern version control systems
• Fluency in English both verbal and written

Nice To Haves

• Practical experience with Azure ML, Databricks, or similar cloud-native ML platforms
• Solid theoretical and practical understanding of common machine learning algorithms, deep learning techniques, and statistical modeling
• Experience collaborating with software engineers to build production-grade software that integrates and leverages advanced Machine Learning technologies (e.g., RAG systems, fine-tuned LLMs, language embeddings)
• Deep understanding of the relationship between data and machine learning models
• Experience with larger scripting projects that involve combining language data from different sources, computing complex metrics over large datasets, etc
• Knowledge of basic C# (or willingness to learn)
• Experience working with legal contracts
• Demonstrated ability to learn and apply new technologies and tool sets with intellectual curiosity
• Experience working for a SaaS company
• A strong track record as a self-starter who thrives on ownership and individual/team responsibility
• Commitment to writing high-quality, maintainable, and well-documented code
• Excellent communication and organizational skills

Responsibilities

• Build datasets, sometimes from limited sources, and evaluation for ML systems, working closely with data annotators
• Design pipelines that include modern ML techniques such as RAG, agent frameworks, language embeddings, and LLMs, and do prompt engineering for ML applications
• Support product development with rules directly , prompts, and high quality data, overseeing annotation where needed
• Evaluate the quality of models and product experiences and close the feedback loop for customer-reported AI quality issues
• Communicate with project stakeholders clearly
• Identify best practices and improve procedures across data systems
• Drive and deliver projects from conceptualization through launch and beyond with continual improvement and support
• Design and conduct product experiments
• Work in a dynamic, ambiguous work environment
• Be self-driven and prioritize multiple work streams
• Collaborate seamlessly with cross-functional teams
• Operate within an Agile/Scrum framework, supporting engineers in testing their code using managed datasets and evaluation tools
• Establish and maintain production monitoring for model performance (focusing on AI quality)

Benefits

• Bonus: Sales personnel are eligible for variable incentive pay dependent on their achievement of pre-established sales goals. Non-Sales roles are eligible for a company bonus plan, which is calculated as a percentage of eligible wages and dependent on company performance.
• Stock: This role is eligible to receive Restricted Stock Units (RSUs).
• Paid Time Off: earned time off, as well as paid company holidays based on region
• Paid Parental Leave: take up to six months off with your child after birth, adoption or foster care placement
• Full Health Benefits Plans: options for 100% employer paid and minimum employee contribution health plans from day one of employment
• Retirement Plans: select retirement and pension programs with potential for employer contributions
• Learning and Development: options for coaching, online courses and education reimbursements
• Compassionate Care Leave: paid time off following the loss of a loved one and other life-changing events

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level