Director of Machine Learning
Jobleads-US
- 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
Vacancy posted 5 days ago
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