Technical Support Engineer
CodeRound is hiring for this role for a VC-backed startup.
- Azure
- Troubleshooting
- AWS
- Freshdesk
- TensorFlow
- GCP
- PyTorch
- MLOps
We are seeking a Technical Support Engineer with a strong focus on MLOps to provide enterprise-level assistance to our customers. In this role, you will diagnose and troubleshoot issues related to machine learning models, frameworks, and deployment pipelines. Your goal will be to ensure the seamless operation of ML systems and to assist our clients in leveraging these technologies effectively.
What you'll do
- Ownership of Issues: Take ownership of customer issues related to machine learning applications and see problems through to resolution.
- Research and Diagnosis: Research, diagnose, troubleshoot, and identify solutions for software and hardware issues specifically related to machine learning environments.
- Technical Support: Provide support for ML frameworks (e.g., TensorFlow, PyTorch) and tools (e.g., MLflow, Kubeflow) used in model training and deployment.
- Network Configuration: Assist clients with network configuration issues that may affect ML model performance and data access.
- Remote Support: Use remote desktop connections to provide immediate support and guidance to clients facing technical challenges in their ML workflows.
- Communication: Communicate effectively via email, chat, and phone to provide clear instructions and technical manuals to clients.
- Collaboration: Work closely with the Customer Success Manager and data science teams to ensure seamless support and integration of ML solutions.
- Escalation: Properly escalate unresolved issues to appropriate internal teams, such as data scientists or software developers, when necessary.
- Documentation: Document technical knowledge in the form of notes and manuals, particularly focusing on MLOps best practices and troubleshooting steps.
- Follow-Up: Ensure all issues are properly logged and follow up with clients to confirm their ML systems are fully functional post-troubleshooting.
Must have
Proven Experience: Demonstrated experience as a Technical Support Engineer, MLOps Engineer, or similar role with a focus on machine learning technologies. Hands-On Experience: Proficiency with ML frameworks (e.g., TensorFlow, PyTorch) and familiarity with cloud platforms (e.g., AWS, Azure, GCP) for ML deployment. Technical Troubleshooting: Ability to diagnose and troubleshoot technical issues related to ML model performance, data pipelines, and infrastructure. Remote Desktop Applications: Familiarity with remote desktop applications and help desk software (e.g., Freshdesk) for efficient support delivery. Problem-Solving Skills: Excellent problem-solving and communication skills, with the ability to explain complex technical concepts in simple terms. Educational Background: BS degree in Information Technology, Computer Science, Data Science, or a relevant field.
Good to have
Certifications: Additional certifications in machine learning, cloud computing, or relevant technologies (e.g., AWS Certified Machine Learning, Google Cloud Professional Data Engineer) are a plus.