Director of Machine Learning

Jobtailor; Washington (District of Columbia); On-site; USD 180,000 - 260,000; Full time

Job summary

Jobtailor is seeking a Lead Machine Learning Engineer to steer a high-performing team in Washington, DC. You will architect scalable AI systems, oversee the full data lifecycle from acquisition to inference, and drive performance optimizations.

Expect close collaboration with Product, Customer Success, DevOps, and QA to ensure delivery aligns with customer commitments. The role requires building production-grade AI solutions, mentoring engineers, and guiding the roadmap while communicating ROI

Qualifications

• U.S. Secret Security Clearance required or in process.
• Willing to upgrade to TS/SCI clearance if needed.
• Degree in Computer Science or related field.
• 8+ years of software engineering experience.
• Experience deploying software into production.
• Experience shipping AI/agentic systems and GPU offloading.
• Full-stack development, DevSecOps, and AI systems understanding.
• Proficiency with Docker, Kubernetes, Git and the Python data stack.
• Willing to travel to customer locations as needed.

Responsibilities

• Lead the Machine Learning Engineering team and mentor engineers.
• Architect robust, scalable applications using sound engineering principles.
• Manage the complete data lifecycle from acquisition to inference and postprocessing.
• Improve runtime performance and optimize data access patterns for responsive apps.
• Collaborate with Product, Customer Success, DevOps, and QA to align deliverables with commitments.
• Address issues across Delivery and Platform teams and influence the roadmap.
• Set the technical hiring bar and guide team growth.
• Communicate progress, risks, and ROI, linking AI outputs to revenue and mission impact.

Skills

Machine Learning Leadership

Production Deployment

Python Proficiency

Technical Communication

Collaboration

Mentoring

Full-Stack Development

DevSecOps

AI System Design

Education

Degree in Computer Science or related field

Tools

Docker

Kubernetes

Git

Python Data Stack

Pandas

NumPy

Scikit-learn

PyTorch

Matplotlib

Spark

Job description

• Lead the Machine Learning Engineering team
• Architect robust, scalable applications using sound engineering principles
• Manage the complete data lifecycle from acquisition through model inference and postprocessing
• Improve runtime performance and optimize data access patterns for responsive applications
• Collaborate with Product, Customer Success, DevOps, and QA to align engineering deliverables with customer commitments
• Address key issues across Delivery and Platform teams and identify pain points for roadmap influence
• Set the technical hiring bar and mentor engineers
• Communicate technical progress, risks, and ROI, linking AI team output to revenue and mission impact

Requirements

• Must hold at least a U.S. Secret security clearance
• Must be willing to upgrade to a TS/SCI clearance if needed
• Must be willing to travel to customer locations as needed
• Degree in Computer Science or a related field
• 8+ years of software engineering experience
• Strong software engineering and production deployment background
• Proven track record deploying software into production environments
• Experience shipping production-grade AI/agentic systems
• Experience offloading AI compute to GPUs
• Comfortable designing training and inference pipelines
• Understanding of full-stack software development, DevSecOps, and AI systems holistically
• Familiarity with Docker, Kubernetes, and Git
• Proficiency in Python and the Python Data Stack, including pandas, NumPy, scikit-learn, PyTorch, and Matplotlib
• Experience working with structured and unstructured data from diverse sources
• Preferred: experience building and cultivating a high-functioning Machine Learning Engineering team
• Preferred: experience contributing to engineering excellence and top-tier engineering experience
• Preferred: experience with Spark, Databricks, Snowflake, or similar big data technologies

Core Competencies

Demonstrates expertise in leading Machine Learning Engineering teams, architecting scalable applications, and managing the complete data lifecycle. Proficient in deploying production-grade AI systems and optimizing performance while collaborating across teams to align engineering deliverables with business objectives.

Highest-signal resume keywords

• Machine Learning Engineering Leadership
• Production Deployment Experience
• Python Proficiency
• AI System Design
• Data Lifecycle Management

ATS Optimization Keywords

Hard Skills

• Software Engineering
• AI/Agentic Systems Deployment
• Training and Inference Pipeline Design
• Full-Stack Software Development
• DevSecOps
• Data Processing
• Performance Optimization
• Machine Learning Frameworks
• Big Data Technologies
• Security Clearance Management

Soft Skills

• Mentoring
• Technical Communication
• Collaboration

Certifications & Qualifications

• U.S. Secret Security Clearance
• TS/SCI Clearance (Willingness to Upgrade)

Industry Keywords

• Machine Learning
• AI Systems
• Data Lifecycle
• Production Environments
• Engineering Excellence

Tools & Technologies

• Docker
• Kubernetes
• Git
• Python Data Stack
• Pandas
• NumPy
• Scikit-learn
• PyTorch
• Matplotlib
• Spark