Job Description
Role: Senior Machine Learning Engineer
Experience Level: 3 to 6 Years
Work location: Bangalore, Mumbai & Trivandrum
Notice Period: Looking for candidates can join immediately/Serving Notice Period candidates.
Role & Responsibilities:
As a Senior Machine Learning Engineer, you will be instrumental in developing and deploying cutting-edge AI/ML solutions for our critical projects, moving beyond proof-of-concepts to production-scale systems. Your key responsibilities will include:
- Developing and deploying end-to-end AI/ML solutions for complex use cases, ensuring they are robust, scalable, and production-ready.
- Defining and implementing robust integration strategies between legacy control software (e.g., VB6) and modern Azure ML platforms, ensuring seamless data flow, scalability, and strict data security governance.
- Architecting, developing, and deploying advanced machine learning and deep learning models specifically for curve prediction and automated quality scoring.
- Designing and implementing sophisticated optimization engines to automate precision movements (e.g., lens adjustments) with micron-level accuracy.
- Leading the transition from manual operator heuristics and rule-based systems to automated, data-driven logic and decision-making processes.
- Performing extensive data pre-processing on historical calibration data to train and validate models, and building robust production monitoring, alerting, and retraining scripts.
- Continuously enhancing, modifying, optimizing, and maintaining existing ML models to improve performance, accuracy, and efficiency.
- Working closely with external and internal stakeholders to define requirements for ML use cases, gather feedback, and drive solution enhancements.
- Generating actionable insights from large datasets and effectively communicating complex analysis results and model performance to clients and internal stakeholders.
Skills Expectation:
We are looking for a highly skilled and analytical Senior Machine Learning Engineer with a strong background in
both traditional ML and deep learning, coupled with practical experience in deploying and managing models in
production.
- Hands-on coding experience, fluent in Python and SQL.
- Experience with PySpark for large-scale data processing.
- Expertise in Tree-based models (e.g., XGBoost, LightGBM).
- Strong foundation in Traditional ML algorithms (e.g., Logistic Regression, Cluster Analysis, Decision Trees, Statistical Modeling, Predictive Analysis, Regression, Classification).
- Experience with Encoder-Decoder architectures for sequence modeling.
- Proficiency in Deep Learning Architectures specifically for time series and curve data.
- Familiarity with sequence modeling approaches in Deep Learning.
- Experience in Time Series forecasting using algorithms such as ARIMA, SARIMA, Prophet, etc
- Experience with advanced optimization techniques for black-box functions, including Bayesian Optimization and sophisticated hyperparameter tuning methods.
- Familiarity with Azure environments and Azure ML services.
- Experience with Databricks for ML workflows and data engineering.
- Must have experience in putting models into production.
- Experience in post-production deployment, including MLOps practices (monitoring, retraining, versioning), would be a significant plus.
- Experience working with scalable, highly-interactive, high-performance ML systems and projects.
- Great analytical skills with meticulous attention to detail.
- Strong stakeholder and team management skills.
Note: Please apply to the job if currently seving Notice Period or can join immediately, we are accepting immedaite joiners only.