We are looking for a powerhouse Machine Learning Engineer to bridge the gap between cutting-edge research and global production. In this role, you will own the end-to-end deployment pipeline that scales our sophisticated time-series forecasting engine into new international markets.
If you love taking complex models out of the lab and building the rugged, scalable infrastructure needed to power them in the real world at a global scale, this is your next big challenge.
Essential functions
- Own the end-to-end DS/ML project lifecycle from initial research to robust production deployment phases
- Build and sustain deployable statistical and machine learning models, mostly for time series forecasting in the context of integrated business planning
- Manage and optimize legacy code while collaborating closely with both core developers and business-side stakeholders
- Design, implement, and enhance high-quality feature engineering pipelines and data processes
Qualifications
- Production ML Experience: Proven ability to successfully transition, deploy, and scale statistical and ML models in a production environment.
- Core Technical Stack: Deep proficiency in Python and PySpark, along with model lifecycle tracking tools like MLflow.
- Cloud Ecosystem: Strong hands-on experience with cloud development using AWS, GCP, or Azure providers .
- ML & Data Fundamentals: Solid understanding of ML algorithms and core Python packages (TensorFlow, PyTorch, scikit-learn, XGBoost, LightGBM, pandas, NumPy, SciPy) with strong knowledge of feature engineering.
- Systems & Collaboration: Solid software engineering background with comfort working on legacy codebases and bridging the gap between developers and the business side.
Would be a plus
- Experience with AI application development or production-level AI tool deployment.
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.