Sr Machine Learning Engineer
$135,200–$181,200 year
On-siteOrlando, Florida, United States
Job Summary
Design and run CI/CD pipelines, model versioning, and automated deployment workflows to move AI systems from experimentation to production. Stand up comprehensive observability infrastructure for model performance, drift, data quality, and latency with automated remediation. Develop production-scale agentic workflows and multi-agent orchestration platforms while establishing evaluation frameworks for Large Language Models and safety guardrails. Drive the complete AI/ML lifecycle including implementation, testing, and continuous operational monitoring in collaboration with cross-functional stakeholders. Provide hands-on technical leadership on architectural decisions and resolve complex technical blockers to maintain project velocity.
Required Qualifications
- 5+ years of proven expertise in designing, building, and deploying AI/ML solutions at scale
- 1–2 years of production experience in Generative AI technologies
- Comprehensive MLOps/LLMOps experience with hands-on implementation of CI/CD pipelines, model and agent monitoring, versioning, observability, and lifecycle management in production
- Production deployment experience on major cloud platforms (AWS, Azure, or GCP)
- Expert-level programming proficiency in Python and AI/ML development ecosystems
- Strong foundation in machine learning including statistical modeling, supervised and unsupervised learning algorithms
- Advanced skills in prompt engineering with a deep understanding of optimization techniques and best practices for LLM interactions
- Versatile ML skillset spanning traditional techniques (classification, regression, clustering) and cutting-edge deep learning approaches
- Production-grade Generative AI experience deploying and maintaining LLMs and multi-modal models in live environments
- Exceptional analytical capabilities with a track record of solving complex technical problems and thriving in ambiguous, rapidly-evolving situations
- Outstanding communication and collaboration skills with the ability to translate complex technical concepts for diverse audiences and drive cross-functional alignment
- Proven ability to influence and lead in matrix organizations where collaboration and relationship-building are essential to achieving outcomes
- Bachelor's degree in Computer Science, Machine Learning, Mathematical Sciences, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study, and/or equivalent work experience
Desired Qualifications
- Experience with container orchestration and infrastructure-as-code (Docker, Kubernetes, Terraform) for ML workloads
- Experience with vector databases and embedding technologies
- Master's degree or Ph.D in Artificial Intelligence, Machine Learning, Mathematical Sciences, Computer Science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study, and/or equivalent work experience
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