Job Description: ML Engineer (Time Series)

Job Title: ML Engineer Time Series

Immediate Joiners Preferred

Experience: 3 - 8 Years

Location: Bengaluru (Bengaluru Based Candidates)

About the Role

We are looking for a skilled Machine Learning Engineer with strong experience in Time Series algorithms, Python, and machine learning to join our team in Bengaluru. The ideal candidate will have hands-on experience developing, deploying, and optimizing time series models and will work closely with Data Scientists and other engineering teams to deliver scalable ML solutions.

Key Responsibilities

- Develop, implement, and optimize time series forecasting and machine learning models.
- Work with large and complex datasets to identify trends, patterns, seasonality, and anomalies.
- Apply time series techniques such as ARIMA/SARIMA, Exponential Smoothing, Prophet, regression-based forecasting, and advanced ML/DL approaches.
- Build robust data preprocessing, feature engineering, model training, validation, and evaluation pipelines using Python.
- Collaborate closely with Data Scientists, Data Engineers, and business stakeholders to translate business problems into ML solutions.
- Evaluate model performance using appropriate forecasting and statistical metrics.
- Productionize ML models and contribute to scalable and maintainable ML pipelines.
- Monitor model performance and identify opportunities for model improvement and retraining.
- Write clean, reusable,



and well-tested Python code.
- Document methodologies, experiments, model assumptions, and results.

Required Skills

- 3 - 8 years of experience in Machine Learning, Data Science, or a closely related field.
- Solid programming skills in Python.
- Hands-on experience with Time Series analysis and forecasting algorithms.
- Good understanding of:
- Time series decomposition
- Trend and seasonality
- Stationarity
- Autocorrelation and partial autocorrelation
- Forecasting and model validation
- Feature engineering for time-dependent data

- Experience with ML libraries such as Scikit-learn, Pandas, NumPy, Statsmodels, or equivalent.
- Strong understanding of machine learning concepts, model evaluation, and statistical methods.
- Experience working with Data Scientists and translating analytical models into production-ready solutions.
- Strong problem-solving and analytical skills.

Good to Have

- Experience with deep learning for time series, including LSTM, GRU, Transformers, or Temporal Fusion Transformer.
- Exposure to MLOps/model deployment and cloud platforms such as AWS, Azure, or GCP.
- Experience with Docker, Kubernetes, MLflow, Airflow, or similar technologies.
- Knowledge of SQL and data engineering concepts.
- Experience with anomaly detection, demand forecasting, predictive maintenance, or similar time-dependent use cases.
- Exposure to CI/CD and production ML systems.

📌 ML Engineer (Bengaluru)
🏢 Bct Consulting
📍 Bengaluru