Senior ML Engineer

We are looking for Senior ML/AI Engineer who will focus heavily on deploying complex Natural Language Processing (NLP), Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) frameworks to build high-performance, compliant, and domain-specific expert SaaS applications.

Requirements

• Programming: Advanced mastery of production-grade Python (clean, modular, and performant code architecture) and structured database querying using SQL.
• Frameworks & Core AI: Deep hands-on experience with modern frameworks like PyTorch or TensorFlow, alongside LLM tools (e.g., Hugging Face Transformers, LangChain, LlamaIndex, or GenAI orchestration APIs).
• Cloud Infrastructure: Proven experience deploying enterprise-level ML workflows natively inside public cloud ecosystems, specifically Microsoft Azure or AWS (e.g., Azure ML, SageMaker, AWS Bedrock).
• Containerization & Orchestration: Solid proficiency with Docker and Kubernetes for deploying models reliably at scale.
• Data Engineering Pipelines: Familiarity building complex data ingestion workflows using modern tools (e.g., Apache Airflow, Prefect, Databricks, or Spark).

Responsibilities

• Production Deployment & MLOps: Architect, scale, and maintain automated ML pipelines, feature stores, and inference engines within cloud infrastructures.
• Generative AI & Agentic Workflows: Implement, fine-tune, and optimize LLM-driven features and AI agents, ensuring data lifecycle tracking, guardrails, and optimal context windows.
• Model Monitoring & Telemetry: Design and enforce end-to-end monitoring solutions to detect data drift, evaluate inference performance, track model decay, and optimize for cost and speed.
• Cross-Functional Collaboration: Partner directly with AI Researchers, Data Engineers, and Product owners to transform proof-of-concepts into low-latency, scalable microservices.
• Software Excellence: Enforce rigorous software engineering principles (CI/CD, unit/integration testing, robust system design, clear documentation) and provide technical leadership and mentorship to junior and mid-level engineering team members.

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.