Staff Machine Learning Engineer

We are looking for a Staff Machine Learning Engineer to join a fast-paced and innovative project transforming how software teams manage requirements and system design. Our client’s platform leverages AI to automatically build structured knowledge models from natural language specifications, bringing clarity to developers and intelligence to AI tools.

In this Staff-level role, you won't just be training models, you will be architecting and scaling production-grade ML systems, building agentic frameworks, and driving the technical vision for our core AI capabilities.

Responsibilities:

• Architect AI Solutions: Design, deploy, and scale advanced ML systems and LLM-driven agents to process natural language into structured knowledge models.

• Build Agentic Frameworks: Utilize tools like LangChain to create intelligent, autonomous workflows that enhance software design processes.

• Drive MLOps Excellence: Build and maintain robust MLOps pipelines covering CI/CD, model versioning, deployment, and comprehensive ML system observability.

• Scale Backend Infrastructure: Deploy containerized ML services using Kubernetes on GCP, integrating them with event-driven architectures (Kafka) and relational/graph databases.

• Bridge Technologies: Work seamlessly in a polyglot environment, bridging Python-based ML services with Kotlin backend systems.
  

Min requirements:

• Production ML: Proven, deep experience building, deploying, and maintaining Machine Learning systems in production environments at scale.

• LLMs & Agents: Strong hands-on experience working with Large Language Models and building agentic frameworks (LangChain or similar).

• Python Mastery: Advanced Python skills specifically tailored for ML services, orchestration, and tooling.

• MLOps & CI/CD: Deep understanding of MLOps concepts, including pipeline creation, monitoring, versioning, and automation using GitHub Actions.

• Cloud & Containerization: Solid experience with Kubernetes and cloud platforms (GCP preferred).

• Backend & Architecture: Strong understanding of backend systems, APIs, database management (Postgres), and event-driven architectures (Kafka or similar).

Would be a plus:

• Experience with Graph-based reasoning, Knowledge Graphs, or Graph databases.

• Prior work focusing on agent evaluation, benchmarking, or LLM cost optimization.

• Exposure to Kotlin and building/maintaining Kotlin backend services.

• Previous experience building internal AI platforms or developer tooling.

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.