Forward Deployed Engineer

Marathon TS; Washington (District of Columbia); On-site; USD 140,000 - 210,000; Full time

Job summary

Marathon TS in Washington, DC area seeks a senior engineer to turn loosely defined customer needs into production-grade data, evaluation, and ML-assisted workflows for advanced AI systems. You will own the full lifecycle of AI data pipelines, building tooling that makes human-in-the-loop data generation and review faster, more reliable, and higher quality.

The role sits at the intersection of data science, data engineering, AI engineering, and delivery operations.

Qualifications

• 5+ years in data science, data engineering, ML engineering or similar roles.
• Strong hands-on experience with Python and SQL data tooling.
• Familiar with ML/LLM solutions and production workflows.
• Track record turning ambiguous requirements into technical specs and delivery.

Responsibilities

• Build and deploy evaluators and design quality measurement systems that validate outputs.
• Generate synthetic datasets by developing new pipelines or adapting existing ones to speed up engagements.
• Package and deliver production-grade datasets with standardized formatting, documentation and QA.
• Build custom applications and tooling for non-standard customer requirements.
• Define production specifications and workflows and secure technical alignment with customer teams for go-live.
• Act as the technical point of contact for delivery leads, resolving blockers and supporting discussions.
• Maintain consistency of specifications across customer and internal teams.
• Document best practices and spot automation opportunities to improve delivery.
• Run model benchmarking and maintain solution leaderboards to show capability.
• Improve evaluation frameworks, assets and delivery processes to raise speed, quality and scale.

Skills

Python

SQL

ML engineering

Data pipelines

APIs

Tools

APIs

Model benchmarking

Job description

You'll work on projects that shape real production AI systems, creating the training and evaluation data behind the next generation of large language models and AI agents. You'll own technical data workflows end-to-end and help shape how the delivery team works as it grows.

About the Role

We're looking for a senior engineer to turn loosely defined customer needs into production-grade data, evaluation, and ML-assisted workflows for advanced AI systems. You'll own the full lifecycle of AI data pipelines: building and deploying the ML-based tooling that makes human-in-the-loop data generation and review faster, more reliable, and higher quality.

The role sits where data science, data engineering, AI engineering, and delivery operations meet. You'll work closely with delivery and operations teams and with customer technical stakeholders. You'll write technical specifications, design evaluation workflows, set quality standards, and build the applications that keep projects moving.

This role suits someone comfortable across the whole delivery lifecycle, likes solving messy multi-part problems hands-on, communicates clearly to technical and non-technical audiences, and works well on a team.

What You'll Do

Project Execution and Delivery

• Build and deploy evaluators, and design quality measurement systems that validate outputs and confirm deliverables meet customer expectations
• Generate synthetic datasets by developing new pipelines or adapting existing ones to speed up engagements and augment training data
• Package and deliver production-grade datasets with standardized formatting, thorough documentation, and quality assurance
• Build custom applications and tooling for non-standard or specialized customer requirements

Production and Technical Partnership

• Define production specifications and workflows, and secure technical alignment with customer teams for smooth go-live transitions
• Act as the technical point of contact for delivery leads, answering complex questions, resolving blockers, and supporting customer discussions
• Keep specifications consistent across customer and internal teams throughout each engagement
• Document best practices and spot automation opportunities, working with engineering to keep improving delivery

Technical Leadership and Innovation

• Run model benchmarking on existing datasets and maintain solution leaderboards that show technical capability
• Keep improving evaluation frameworks, technical assets and delivery processes to raise speed, quality and scale

What We're Looking For

• 5+ years in data science, data engineering, ML engineering, solutions engineering, forward-deployed engineering or similar technical roles
• Strong hands-on experience with Python and SQL data tooling
• Familiarity with ML and LLM-based solutions, including applying ML in production and building validation, evaluation or quality measurement workflows for ML/LLM systems
• A track record of turning ambiguous requirements into technical specifications, workflows and delivered solutions
• Experience integrating systems through APIs and building custom tooling for non-standard needs