Ontrac Solutions is seeking a highly skilled Staff-Level ML Architect to support an urgent staff augmentation engagement for one of our clients.
This is a highly technical, hands-on leadership role for someone who can operate as both the technical anchor for an ML engineering pod and the strategic bridge to senior Product, Engineering, and Data leadership.
The ideal candidate has deep experience architecting and deploying production-grade AI/ML systems, leading small technical teams, and establishing reliable MLOps patterns in complex environments. This person will be expected to stay hands-on with the code while also helping manage stakeholder alignment, technical direction, and execution priorities.
Required Credentials
- 8+ years of experience in machine learning, software engineering, data engineering, or related technical roles.
- 3+ years of experience in a senior, staff-level, architect, or technical lead capacity.
- Bachelor's degree in Computer Science, Engineering, Data Science, Machine Learning, or equivalent practical experience.
Required Qualifications
- Strong hands-on experience architecting, building, and deploying production-grade AI/ML systems.
- Deep expertise with LLMs, agentic workflows, AI agents, tool-calling, sub-agents, and fine-tuned foundation models.
- Experience using or integrating with Model Context Protocol (MCP) in production or near-production environments.
- Strong architectural knowledge of the GCP ecosystem, including Vertex AI and modern MLOps pipelines.
- Experience with MLOps tools and patterns, including Spark, Airflow, CI/CD, model deployment, monitoring, and governance.
- Proficiency with real-time inference optimization tools and patterns, including Triton or similar technologies.
- Strong Infrastructure-as-Code experience, preferably with Terraform.
- Ability to lead and mentor a pod of ML engineers while remaining highly hands-on with design, implementation, code review, and deployment.
- Strong communication skills with the ability to translate complex technical requirements and constraints for non-technical stakeholders.
- Proven ability to protect engineering teams from scope creep, organizational friction, and unclear priorities while maintaining strong stakeholder alignment.
Key Responsibilities
- Serve as the hands-on technical lead for a pod of three ML Engineers supporting a large-scale digital product platform.
- Architect, build, and deploy advanced AI systems using raw and fine-tuned LLMs, AI agents, sub-agents, tool-calling, and MCP integrations.
- Establish and enforce reliable MLOps deployment patterns, coding standards, architecture standards, and engineering best practices.
- Partner closely with Product, Engineering, Data, and senior leadership to shape AI/ML strategy and execution priorities.
- Provide technical direction, code-level guidance, and architectural oversight across the ML engineering pod.
- Act as a project and program management buffer for the technical team, helping manage roadmap alignment, stakeholder communication, and delivery expectations.
- Ensure production AI/ML systems are scalable, maintainable, secure, observable, and aligned with business and product goals.
Preferred Qualifications
- Prior experience supporting consumer-facing platforms, marketplace products, social platforms, or other high-scale digital products.
- Experience working in fast-moving staff augmentation, consulting, or client-facing technical environments.
- Experience balancing executive-level communication with deep technical execution.
- Prior experience leading urgent or high-priority AI/ML transformation initiatives.
About Ontrac Solutions
Ontrac Solutions is a strategic consulting and technology solutions firm helping companies innovate, create, and elevate through digital product consulting, cloud solutions, AI-based data solutions, and staff augmentation. We partner with clients to bring the right technical expertise, execution support, and strategic guidance to complex business and technology initiatives.