Staff Machine Learning Engineer - Team Lead (Active Secret Clearance)
Quick Summary
This position is listed on behalf of a partner company, who manages all applications and next steps.
Join a mission-driven engineering team developing advanced AI systems for complex, real-world government applications. In this senior technical leadership role, you will combine hands-on machine learning engineering with customer-facing collaboration, guiding solutions from initial design and data preparation through deployment and delivery. You will tackle challenging technical problems, shape production-ready systems, and help ensure AI models remain reliable, effective, and trustworthy beyond testing environments. Working closely with engineers, customers, and cross-functional teams, you will provide technical direction, mentor colleagues, and translate complex requirements into practical outcomes. The role offers a remote or hybrid working arrangement based out of Austin, Texas, with opportunities to engage directly with customers and contribute to impactful projects.
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Lead the design, development, and delivery of complex, production-level machine learning and AI solutions, from data shaping and analytics to end-user implementation.
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Serve as a hands-on technical contributor while providing leadership and guidance across engineering teams and customer environments.
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Define project scope, establish technical plans, coordinate resources, and drive execution through successful delivery.
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Build, train, evaluate, optimize, and deploy machine learning models for real-world applications.
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Design and implement algorithms, data structures, production analytics, and software architectures using appropriate engineering patterns and cloud technologies.
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Collaborate directly with customers to understand their challenges, translate feedback into technical requirements, and shape future solutions.
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Communicate technical concepts clearly and professionally to engineering teams, customers, and other stakeholders.
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Mentor and support engineers, fostering strong technical practices and effective collaboration across distributed teams.
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Travel to customer locations or project environments as required, with travel of up to 25%.
Requirements
~1 min read-
Advanced degree in Data Science, Machine Learning, Computer Science, or a related discipline, along with at least 10 years of relevant professional experience.
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Demonstrated ability to lead, manage, and mentor cross-functional engineering teams across office-based, remote, and customer-facing environments.
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Proven experience defining, scoping, planning, and executing complex technical solutions in production environments.
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Excellent communication and stakeholder-management skills, including the ability to explain sophisticated technical topics clearly.
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Broad proficiency in programming languages used in machine learning, with strong expertise in Python and at least one systems programming language.
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Strong knowledge of algorithms, data structures, production analytics, software design patterns, and cloud-based development.
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Extensive experience building, training, evaluating, and/or optimizing the deployment of machine learning models.
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Proficiency with modern software engineering tools, workflows, and development practices.
Willingness and ability to travel up to 25% of the time.
Additional experience that would be valuable:
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Kubernetes (K8s) and horizontally scaled architectures.
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Messaging and streaming technologies such as NATS, Kafka, or RabbitMQ.
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Development of AI agents and agentic workflows.
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Working with complex and varied data types.
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Delivering technology solutions in secure government environments.
What We Offer
~1 min readLocation & Eligibility
About this job
- Pay per year
- $230,000–$280,000 a year
- 22% above the $208,788 median for Machine Learning Engineer jobs on Jobera (1,008 salaries).
- Who can apply
- United States
- Posted
- Today
Listing Details
- Posted
- November 5, 2026
- First seen
- November 5, 2026
- Last seen
- November 5, 2026
Posting Health
- Days active
- -1
- Repost count
- 0
- Trust Level
- 80%
- Scored at
- November 5, 2026
Signal breakdown
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