Senior Software Engineer - Machine Learning

The Trade Desk•Bellevue, WA

53d

About The Position

At The Trade Desk, we design and build custom solutions that extend our platform's capabilities, with a focus on quality, reusability, and customer success. From client facing applications and backend services to data science models, workflow automation, reports, and large-scale data workflows, we deliver end-to-end systems that drive advanced campaign optimization, actionable analytics, and robust data operations at global scale.We are a small, high impact team that strategically enables advertisers to unlock advanced capabilities, we solve unique partner needs, shape technical patterns that benefit the wider platform. Whether it's enabling advanced bidding strategies, streamlining data pipelines, or creating bespoke reporting experiences, we build with quality and scale in mind.We value a culture of collaboration, innovation, and learning. Here, engineers invent and simplify as they extend platform capabilities, striking the right balance between reusability and customization while partnering closely with clients and cross functional teams. What you'll do: This role is ideal for someone passionate about building innovative, data-driven solutions in the programmatic advertising space. You thrive in a high-scale, data-intensive environment where client needs are diverse, and you will play a key role in designing reusable patterns and standardized components that accelerate future solution delivery.We're looking for a Senior Software Engineer who combines deep software engineering expertise with strong statistical and data analysis skills to lead the development of data-driven systems and solutions. This role blends software engineering excellence, machine learning development, and production-grade MLOps - ideal for someone who enjoys bridging the gap between model experimentation and deployment at scale. You'll work closely with data scientists, ML engineers, and product teams to develop ML pipelines, optimize data workflows, automate deployment processes, and ensure that machine learning models deliver real-world value reliably and efficiently.In addition to the core responsibilities as Software Engineer, you will specifically:

Requirements

Deep experience designing and building large-scale, distributed systems across client-facing applications, backend services, and data workflows
Proven ability to own architecture and technical direction for complex, end-to-end systems
Strong knowledge of data processing frameworks and workflows, with experience scaling systems for data-intensive workloads
Strong experience developing, testing, and optimizing predictive models and statistical algorithms
Expertise in big data processing and analytics frameworks - including tools like Apache Spark, Kafka, Airflow, Hadoop, Snowflake, and distributed data storage systems (S3, BigQuery, Redshift, or Delta Lake)
Proficiency in one or more programming languages such as Python, Java, C#, or Scala
Experience deploying ML frameworks (TensorFlow, PyTorch) for large-scale data pipelines
Strong communication skills for aligning technical decisions with business priorities across technical and non-technical stakeholders
7+ years of software development experience, with significant experience building and scaling production systems
Solid foundation in statistics, optimization and experience applying statistical methods to real-world data
Bachelor's or Master's degree in Computer Science, Engineering, or equivalent experience

Responsibilities

Drive architecture and design for end-to-end systems within Custom Solutions, influencing platform patterns and best practices across teams
Develop custom APIs and backend services that integrate seamlessly with the core platform
Optimize data storage, retrieval, and API performance for global-scale programmatic workloads
Apply best practices in software engineering across the stack for scalability, maintainability, and resilience
Create and maintain data processing workflows and automation solutions to support large-scale advertiser operations
Collaborate with data scientists to integrate productionized models and algorithms into production-ready systems for advanced bidding and analytics
Design and optimize large-scale data pipelines supporting ML workflows
Establish and enforce Engineering and MLOps best practices across our teams
Implement monitoring, logging, and observability across frontend and backend systems to maintain reliability and performance
Identify opportunities to standardize patterns to accelerate future solution delivery

Benefits

comprehensive healthcare (medical, dental, and vision) with premiums paid in full for employees and dependents
retirement benefits such as a 401k plan and company match
short and long-term disability coverage
basic life insurance
well-being benefits
reimbursement for certain tuition expenses
parental leave
sick time of 1 hour per 30 hours worked
vacation time for full-time employees up to 120 hours thru the first year and 160 hours thereafter
around 13 paid holidays per year
Employees can also purchase The Trade Desk stock at a discount through The Trade Desk's Employee Stock Purchase Plan