Senior ML Engineer
2 days ago
- 5+ years with Azure (ML pipeline components), Azure Databricks, Azure DevOps.
- Proven experience of design and deployment of end-to-end ML pipelines.
- Experience with building infrastructure for classic DS models and/or LLM/SLMs.
- 2+ years with orchestration (e.g., Kubeflow, Airflow, Azure Data Factory) and CI/CD for ML.
- Experience deploying containerized ML solutions (e.g. Docker/Kubernetes).
- Knowledge of model and data versioning (e.g. MLflow, DVC).
- Knowledge of MLSecOps (security in the context of MLOps)
- Experience with Infrastructure as a Code (e.g., Terraform, CloudFormation).
Essential Functions
- List of identified areas for improvements for existing PepsiCo project
- Recommendation on:
MLOps practice
MLSecOps
- Sample templates and pipelines
- Recommendation on the infrastructure for:
Classic DS models
LLM solution, primarily focused on fine tuning SLM by domain
- Recommendation on Data Strategy:
JIT access to data for the period of training with security guardrails (access, data masking, etc.)
Qualifications
- Azure Databricks, Azure DevOps.
- ML Ops
- ML SecOps
- Classic DS Model
Would be a plus
- Knowledge of MLOps for LLM/SLM
- Experience in ML system/architecture design (load balancing, caching, failover).
- Knowledge in building scalable, resilient ML architectures.
- Cross-team collaboration experience (data science, engineering, DevOps).
- Experience with monitoring/logging for production models (e.g. Prometheus, Grafana, ELK stack).
We offer
- Opportunity to work on bleeding-edge projects
- Work with a highly motivated and dedicated team
- Competitive salary
- Flexible schedule
- Benefits package - medical insurance, sports
- Corporate social events
- Professional development opportunities
- Well-equipped office
About Us
Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud & DevOps, application modernization and customer experience. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.
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