Staff Engineer
- Grid Dynamics
- 7 - 12 years
- Hyderabad
- 1 month ago
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Job Description
Grid Dynamics wants to build a centralized, observable and secure platform for their ML, Computer Vision, LLM and SLM models. Grid Dynamics wants to onboard a vast number of AI agents, able to cover multiple required skills, ensuring a certain level of control and security in regards to their usage and availability. The observable platform must be vendor-agnostic, easy to extend to multiple type of AI applications and flexible in terms of technologies, frameworks and data types.
This project is focused on establishing a centralized LLMOps capability where every ML, CV, AI-enabled application is monitored, observed, secured and provides logs of every activity.
The solution consists of key building blocks such monitor every step in a RAG, Multimodal RAG or Agentic Platform, track performances and provide curated datasets for potential fine-tuning.
Alignment with business scenarios, Grid Dynamics provides also certain guardrails that allow or block interactions user-to-agent, agent-to-agent or agent-to-user. Also, Guardrails will enable predefined workflows, aimed to give more control over the series of LLM chains.
Essential functions
Job Role: Lead MLOps Engineer
Location: Hyderabad/Bangalore/Chennai
Experience: 7+ Years
Roles & Responsibilities: Location: Hyderabad/Bangalore/Chennai
Experience: 7+ Years
- Chunking (primarily focused on VectorDB storage).
- Document Parsing and OCR
- Document Parsing with VLMs (Vision Language Models)
- Function Calling with LLMs
- Retrieval Augmented Generation
- Traditional Search (BM25, NER based parsers, Keyword based search index)
- Semantic Search (Embeddings, Embedding models)
- Fine Tuning using LoRA
- Merging multiple LoRA adapters using MergeKit
- Quantising LLMs
- Prompt Engineering techniques
- 4+ 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.
- 4+ 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).
- 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).
Qualifications
- 7+ years in ML Ops / DevOps / data engineering
- Strong Python skills, plus experience with MLflow, Kubeflow, or Airflow
- Hands-on with Docker, Kubernetes, and cloud platforms
- Knowledge of data and model versioning tools (e.g., DVC, MLflow)
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
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Engineering - Software & QARole Category: Software DevelopmentRole: Search EngineerEmployement Type: Full timeContact Details:
Company: Grid DynamicsLocation(s): Hyderabad+ View Contact
Keyskills: System architecture Computer vision Usage orchestration data science devops Architectural design Medical insurance Load balancing Python
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