Manager, AI Engineering
Anaplan View all jobs
- Gurgaon, Haryana
- Permanent
- Full-time
- Lead the technical design, development, and deployment of high-performance time series forecasting algorithms.
- Provide hands-on coding and architectural leadership, establishing best practices for building and validating forecasting models.
- Mentor a team of AI/ML engineers and developers, fostering deep expertise in forecasting techniques and elevating the team's technical capabilities.
- Drive the research and implementation of state-of-the-art forecasting algorithms to continuously improve model accuracy and performance.
- Own the end-to-end lifecycle of forecasting models, including MLOps, CI/CD, deployment, and monitoring in a production cloud environment.
- Collaborate with product managers and researchers to define the technical roadmap for the Forecaster team.
- Lead by example through rigorous code reviews, technical deep dives, and a commitment to engineering excellence.
- Deep Expertise in Time Series Forecasting Algorithms
- Extensive hands-on experience with a wide range of models, including:
- Classical methods (e.g., ARIMA, SARIMA, ETS).
- Modern statistical models (e.g., Prophet).
- Advanced deep learning architectures (e.g., LSTMs, GRUs, CNNs, DeepAR and Transformer-based models like N-BEATS).
- Strong programming skills in Python and deep familiarity with:
- Core machine learning libraries: scikit-learn, Pandas, NumPy.
- Deep learning frameworks: TensorFlow or PyTorch.
- Forecasting-specific libraries: statsmodels, pmdarima, or Darts.
- Proven track record of leading technical projects and shipping production-grade machine learning systems.
- Solid experience with cloud platforms (AWS, Azure, or GCP) and deploying ML models at scale.
- Strong understanding of modern software engineering principles (testing, CI/CD, version control) and MLOps.
- Master's or Ph.D. in a quantitative field like Computer Science, Engineering or equivalent.
- Experience with probabilistic forecasting and quantifying uncertainty.
- Familiarity with large-scale data processing frameworks like Spark or Dask.
- Experience with managing a diverse team of BE, FE, DS and QA.
- Extend offers to candidates without an extensive interview process with a member of our recruitment team and a hiring manager via video or in person.
- Send job offers via email. All offers are first extended verbally by a member of our internal recruitment team whenever possible and then followed up via written communication.