Loading...
SeniorFull-timeJavaScriptTypeScriptPythonJavaReactAWSKubernetesDockerTerraformMachine Learning
Salary Range
$132,600 - $179,400 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
We are looking for an experienced Machine Learning Engineer to join our Bengaluru team at Cloudflare and help scale the next generation of our AI/ML models. In this role, you will build and operate the pipelines behind AI-driven applications, Agents, and Chatbots that power teams across the company.
Key Responsibilities
- →Deploy, manage & support ML Applications & Services on Kubernetes
- →Understand MLOps landscape and work on introducing new tools and solutions for ML & AI initiatives
- →Partner with Data Scientists, Data Engineers, and internal teams to deliver ML solutions in a globally distributed environment
- →Lead development of efficiencies to boost model training to deployment lead times
- →Understand business/product strategy and align analysis efforts to enable them with data insights
- →Leverage Cloudflare products and services for AI & ML initiatives and applications
- →Use software engineering best practices to publish model scores/insights/learnings at scale
Requirements
- ✓M.S or Ph.D in Computer Science, Statistics, Mathematics, or other quantitative fields
- ✓5+ years of ML Engineering experience with proven industry experience in a large scale environment
- ✓Strong experience in scientific computing using Python with Scikit-Learn & PyTorch or Tensorflow
- ✓Strong experience working with Docker & Kubernetes
- ✓Experience working with ML Platform tools (AirFlow, Argo Workflows, ArgoCD)
- ✓Experience working with Data Scientists to deploy Machine Learning applications
- ✓Experience with Full-stack Web technologies and languages
- ✓Experience with Terraform, Google Cloud Platform, or other public cloud equivalents
- ✓Experience working with CI/CD systems, version control, and DevOps tools
- ✓Experience with Databases such as BigQuery, Postgres, SQLite and ETL/ELT practices
- ✓Strong cross-functional collaboration experience with data engineering and data analysts teams
- ✓Proficiency in large language models and frameworks for implementing GenAI applications
- ✓Strong communication and presentation skills
- ✓Demonstrated ability to design scalable, reliable, and observable systems
- ✓Strong problem-solving and communication skills
- ✓Experience mentoring engineers and contributing to a culture of technical excellence
