ML Architect

Essential functions

• Strategic Leadership: Develop and communicate the generative AI vision and strategy, ensuring alignment with organizational objectives.

• Architecture Design: Architect scalable systems for deploying generative AI applications, integrating them with existing technology stacks.

• Technical Guidance: Provide leadership and mentorship to teams, promoting best practices in generative AI development and deployment.

• Project Management: Oversee the end-to-end process of generative AI solutions from ideation through delivery and operationalization.

• Collaboration: Work closely with stakeholders to identify opportunities for AI-driven solutions and streamline change management processes.

• Performance Monitoring: Monitor, optimize, and troubleshoot production systems to maintain high performance of AI applications.

• CI/CD Pipeline Management: Design and manage continuous integration and continuous deployment pipelines for generative AI solutions.

• API Development: Define and deliver quality API access for various generative AI services.

• Team Development: Recruit, mentor, and coach team members to foster a culture of continuous learning.

Qualifications

Educational Background: Bachelor’s degree with 8+ years of experience; or Master’s degree with 7+ years of experience; or PhD with 3+ years of experience in relevant fields (e.g., Computer Science, Engineering).

Experience: Proven experience as an Enterprise Architect or Solution Architect focusing on AI/ML and generative AI technologies.

Technical Skills:

• Proficiency in programming languages such as Python, R, or Java.

• Hands-on experience with machine learning frameworks like TensorFlow, PyTorch, and libraries for deep learning.

• Strong understanding of generative AI techniques, including deep generative models and reinforcement learning.

• Expertise in CI/CD pipeline design and management, particularly in the context of generative AI.

• Familiarity with cloud platforms (AWS, Azure) and containerization tools (Docker, Kubernetes).

Data Management Skills:

• Experience with data handling, including data cleansing, preprocessing, and storage solutions (e.g., Snowflake).

Beneficial Skills

• Knowledge of large language models (LLMs) such as Microsoft Azure OpenAI (e.g., ChatGPT).

• Understanding of AI agents for decision-making and deployment of complex applications.

• Experience in the commercial domain or specific industry knowledge (e.g., biopharmaceuticals).

Soft Skills

• Exceptional communication and collaboration abilities to work effectively with cross-functional teams.

• Strong problem-solving skills combined with critical thinking to analyze complex challenges.

• Ability to present findings and strategies clearly to leadership and stakeholders.

We offer

• Opportunity to work on cutting-edge projects
• Work with a highly motivated and dedicated team
• Competitive salary
• Flexible schedule
• Benefits package - medical insurance, vision, dental, etc.
• 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.