Technical Lead ML Engineer
New
T
Tria FederalAI/ML technology
100% Remote within the United StatesFull-TimeLead
Salary not disclosed
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Job Details
- Required Skills
- AWSDockerGCPKubernetesMachine LearningMicrosoft AzureCI/CDDeep LearningMLOpsDistributed Systems
Requirements
- Experience with cloud platforms including AWS, Azure, or Google Cloud Platform.
- Experience with MLOps, CI/CD pipelines, Docker, Kubernetes, and distributed systems.
- Strong understanding of data pipelines, model lifecycle management, and scalable AI architectures.
- Experience operating within Agile or DevSecOps environments.
- Excellent communication and stakeholder engagement skills.
- Preferred: experience supporting Intelligence Community, Department of Veterans Affairs, DoD, or federal government programs.
- Preferred: experience with Large Language Models, Generative AI, RAG architectures, and vector databases.
- Preferred: familiarity with AI governance, explainable AI, and responsible AI practices.
- Preferred: experience with Spark, Kafka, Hadoop, or GPU-enabled distributed computing platforms.
- An active/current TS/SCI security clearance is nice to have.
Responsibilities
- Serve as the primary point of contact for AI/ML technical matters with customers and stakeholders.
- Lead the design, development, testing, deployment, and productization of AI/ML technologies.
- Develop and communicate AI/ML strategies and technical roadmaps aligned with customer and mission requirements.
- Design, develop, and optimize scalable machine learning and deep learning models for structured and unstructured data.
- Transform research prototypes into secure, scalable, production-ready enterprise solutions.
- Support NLP, predictive analytics, anomaly detection, computer vision, and generative AI initiatives.
- Develop production-grade AI/ML pipelines, CI/CD workflows, and MLOps capabilities.
- Provide system integration oversight across AI/ML pipelines and enterprise platforms.
- Collaborate with software engineers, cloud architects, cybersecurity teams, and customer stakeholders.
- Mentor AI/ML engineering teams and support workforce planning, staffing, hiring, and professional development.
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