Sr. Machine Learning Engineer
Skills
- Strong Python and data-science library proficiency (Pandas, Scikit-Learn, PyTorch, TensorFlow).
- Experience with MLOps/DevOps: CI/CD, workflow automation, and production deployments.
- Experience deploying and building LLM agents and fine-tuning models.
- Container and orchestration experience (Docker, Kubernetes).
- Model testing, validation, and experiment tracking expertise.
- Ability to work with large-scale data pipelines and distributed compute.
Responsibilities
- Lead end-to-end ML/AI projects from exploration through productization and ongoing maintenance.
- Design and implement scalable ML pipelines for large network and cloud datasets.
- Develop strategies for deploying and fine-tuning large language models and agentic LLM workflows.
- Conduct experiments, analyze performance and resource use, and present results with clear metrics and visualizations.
- Drive ML development best practices: testing, CI/CD, code health, and reproducibility.
- Collaborate across Labs, data science, and product teams to integrate ML into product offerings.
- Work within an Agile team to prioritize, deliver, and iterate on ML use cases.
Education
- Degree in Computer Science, Engineering, Mathematics, or related field, or equivalent experience.
- Demonstrable professional experience building and deploying ML systems.
Benefits
- Competitive salary and equity opportunities
- Flexible remote-first work environment
- Comprehensive benefits package (healthcare and related benefits)
- Professional development and learning opportunities
- Generous paid time off and collaborative, values-driven culture
Average salary estimate
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