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Grid Dynamics
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Staff Engineer

Staff Engineer

Grid Dynamics

7 years

0 Lacs

hyderabad telangana india

Posted:1 day ago| Platform:

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Skills Required

grid ml vision ai security data parsing retrieval tuning engineering azure pipeline databricks design deployment orchestration airflow docker model versioning mlflow code terraform architecture collaboration monitoring logging devops python kubernetes development technology consulting analytics leadership

Work Mode

On-site

Job Type

Full Time

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.

Responsibilities

Job Role: Lead MLOps EngineerLocation: Hyderabad/Bangalore/ChennaiExperience: 7+ Years

Roles & Responsibilities

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).

Requirements

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

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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Staff Engineer