TALPRO INDIA PRIVATE LIMITED
Domino Platform L3 Support / Development Engineer
Be an Early Applicant
Provide L3 support and platform engineering for the Domino Data Lab platform. Troubleshoot production incidents involving workspaces, models, jobs, connectivity, access, and performance; conduct root-cause analysis and implement permanent fixes. Manage upgrades, patching, monitoring, tuning, and reliability for enterprise data science and AI/ML workloads. Support Python and R environments, ML workflows, Kubernetes, Docker, AWS, SageMaker, and Azure Machine Learning integrations in regulated or life sciences environments.
This is a remote position.
Service Tower: Data & AI Platforms / Advanced Analytics
Experience: 7–10 Years
Role Type: L3 Support / Platform Engineering / Development Support
Domain Preferred: Life Sciences / Pharmaceutical / Regulated Environments
Immediate Joiners Only
Budget: Open
Location: Open
Work Mode: Open to all: Remote/Hybrid
We are seeking an experienced Domino Platform L3 Support / Development Engineer to provide advanced technical support and engineering expertise for the Domino Data Lab platform.
The role is focused on ensuring platform stability, performance, availability, and reliability for enterprise-scale Data Science, Advanced Analytics, and AI/ML workloads, particularly in a life sciences or pharmaceutical environment.
The ideal candidate should have strong hands-on experience in supporting data science platforms, troubleshooting complex production issues, managing ML workflow orchestration, and working with cloud-native technologies.
L3 Platform Support & Incident Management
- Provide Level-3 support for complex Domino Data Lab platform incidents escalated from L1/L2 teams.
- Troubleshoot issues related to:
- Workspace provisioning
- Model execution
- Job orchestration
- Data connectivity
- Platform performance
- User access and environment issues
- Workspace provisioning
- Perform detailed root cause analysis (RCA) and implement permanent fixes for recurring issues.
- Ensure incidents and service requests are handled in line with defined SLAs and KPIs.
- Manage day-to-day operations of the Domino Data Lab platform.
- Support platform upgrades, patching, monitoring, performance tuning, and workspace management.
- Ensure high platform availability and uptime for enterprise data science users.
- Monitor platform health and proactively identify reliability or performance risks.
- Support data science environments and tools including:
- Python
- R
- Git
- Data science notebooks and workspaces
- Python
- Enable ML lifecycle activities such as:
- Experimentation
- Model training
- Model execution
- Deployment support
- Experimentation
- Support analytics and AI/ML teams in resolving platform-level blockers.
- Implement automation improvements to reduce manual platform support efforts.
- Enhance monitoring and alerting for platform health, usage, failures, and performance bottlenecks.
- Recommend and implement improvements to increase stability, reliability, and scalability.
- Work with container and orchestration technologies such as:
- Kubernetes
- Docker
- Kubernetes
- Support cloud-based AI/ML platform integrations and workloads across:
- AWS
- Amazon SageMaker
- Azure Machine Learning
- AWS
- Assist with infrastructure-level troubleshooting related to cloud, containers, networking, and compute environments.
Mandatory Technical Skills
- Strong hands-on experience with Domino Data Lab platform.
- Experience supporting data science platforms and ML workflow orchestration.
- Strong troubleshooting and L3 production support experience.
- Hands-on experience with:
- Kubernetes
- Docker
- Python / R environments
- GitHub / GitLab / Bitbucket
- Kubernetes
- Cloud platform exposure, preferably:
- AWS
- Amazon SageMaker
- Azure Machine Learning
- AWS
- Understanding of data science and AI/ML platform operations.
- 7–10 years of overall IT experience.
- Minimum 4+ years supporting data science, analytics, AI/ML, or advanced analytics platforms.
- Experience working in life sciences, pharmaceutical, or regulated environments.
- Familiarity with:
- GxP environments
- ITSM tools
- Change management
- Release management
- Incident and problem management
- GxP environments
- Kubernetes administration experience.
- Domino Data Lab certification.
- Cloud certifications in AWS or Azure.
- Exposure to:
- Clinical analytics platforms
- Research data platforms
- AI/ML model development
- Regulated data science environments
- Clinical analytics platforms
- Strong analytical and problem-solving skills.
- Ability to work independently in high-priority production support situations.
- Good communication and stakeholder management skills.
- Ability to collaborate with data scientists, ML engineers, infrastructure teams, and business stakeholders.
- Strong ownership mindset and ability to work in SLA-driven environments.
- Strong Domino Data Lab hands-on experience is highly preferred.
- Must be comfortable handling L3 platform incidents and RCA.
- Should have experience supporting enterprise AI/ML and data science workloads.
- Life sciences / pharma / GxP experience will be a strong advantage.
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