ML Architect

Essential functions

• Define the end-to-end ML architecture, ensuring scalability, efficiency, and reliability.

• Design data pipelines and MLOps workflows for model training, deployment, and monitoring.

• Choose the right ML frameworks, libraries, and cloud platforms based on business needs.

• Develop strategies for model lifecycle management (training, versioning, updating, and deprecating).

• Ensure architectures are aligned with business objectives and KPIs.

• Build machine learning tooling to facilitate various phases of the ML lifecycle from model training, data ETL, end-to-end model evaluation and deployment

• Work with technical and non-technical stakeholders to build solutions to align LLMs for specific use cases.

• Deliver reusable and easy-to-use tooling to integrate with existing data and machine learning systems.

Qualifications

• Strong understanding of machine learning principles, especially in the context of LLMs.

• 5+ years of proficiency in Python, including machine learning packages like Jax/Tensorflow or PyTorch.

• Skills in Java/scala (preferred).

• Experience building scalable deep learning systems.

• Experience with large scale data infrastructure.

• Strong verbal and written communications skills with the ability to work effectively across internal and external organizations and virtual teams.

• BS/BA or equivalent degree in computer science or similar (preferred).

• Designing scalable, distributed ML systems.

• Experience with microservices, Kubernetes, Docker.

• Knowledge of database technologies: SQL, NoSQL, graph databases.

• Experience with model selection, feature engineering, and hyperparameter tuning.

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.