This project involves a complex, production-grade machine learning solution with ongoing opportunities for enhancement across both traditional data science and emerging foundation model approaches. It requires strong collaboration with technical and business stakeholders, proactive decision-making, and continuous knowledge sharing to drive innovation, scalability, and business impact.
Essential functions
- Collaborate cross-functionally with engineering and business teams to ensure alignment, clarity of requirements, and effective delivery of solutions
- Drive MLOps excellence by proposing, designing, and optimizing system architecture, including refactoring Azure DevOps (ADO) and Azure Data Factory (ADF) pipelines for scalability and reliability
- Enhance SDLC practices by improving overall solution architecture, code quality, and maintainability across the development lifecycle
- Establish and promote best practices by defining and implementing effective ways of working within the project team
- Partner closely with the client’s core team to ensure rapid identification and resolution of bugs, maintaining system stability and performance
Qualifications
- Azure Cloud expertise, including Azure DevOps, Azure Databricks, and Azure Data Factory
- Strong programming skills in Python and PySpark, with experience in multiprocessing and multithreading for scalable data processing
- Deep expertise in machine learning, spanning classical time-series models, gradient boosting/tree-based methods, deep learning, and emerging foundation models for time-series forecasting
- Demonstrated strengths in decision-making and ownership, with a proactive, results-oriented mindset
- Proven ability in knowledge sharing, collaboration, and initiative, contributing to both team growth and project success
- Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related field
Would be a plus
- Experience with AWS cloud services, including designing and deploying scalable data and ML solutions
- Hands-on experience with Databricks Asset Bundles (DAB) for managing, packaging, and deploying Databricks projects across environments
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.