Ai Ml Engineer

AI/ML Engineer

Location: Bangalore

EXP: 5 to 8Yrs

Mandatory skills: Python, Pyspark, SQL, Traditional ML, MLOPS

Job Summary:

The primary purpose of this role is to design, build and maintain the data pipelines  & ML ops systems, conducting experiments & performing statistical analysis, EDA & bringing insights aiding fine-tune models, training & retraining ML models as needed that enable the organization to process large volumes of data & also productionize, scale & manage AI/ML models. The main goal includes support to optimizing model training and inference. This role will harness AI/ML platform capabilities and help accelerate the development of Data & AI/ML driven products.

Roles & Responsibilities:

• Build and maintain data ingestion, transformation, and feature engineering pipelines to support model training and inference.
• Conducting run/experiments & performing statistical analysis, EDA & bringing insights aiding fine-tune models
• Ensure data pipelines are robust, scalable, and compliant with data governance and privacy standards.
• Supporting to optimize pipelines & models for performance & efficiency on cloud/on-prem platforms.
• Work collaboratively with data scientists to understand model requirements and translate them into scalable engineering solutions by building data preprocessing, feature engineering & post processing jobs to ensure that the data used for training the models is of high quality & ready.
• Implement and manage Orchestration systems for Data Pipelines & AI/ML models
• Collaborating with Product team to deliver analytics and reports & insights
• Supports the implementation of security and compliance measures within the AI/ML development process, aligning with company policies and industry regulations.
• Championing best practices and consistently working to enhance our production pipelines to improve reliability, scalability, and efficiency.
• Keeps relevant with the latest technologies and frameworks in AI/ML, suggesting improvements and updates to existing systems..

Years of Experience:

• 5 to 8 years experience in projects/applications powered by AI/ML with large dataset

Required Minimum Qualifications:

• Bachelor's/master’s degree in engineering, Computer Science, CIS, or related field (or equivalent work experience in a related field)

Skill Set Required

• Experience with Data engineering & building Data/ML pipelines for AI/ML Models &  business analytics & insights. 
• Hands-on experience (real-time) & proficiency in building robust, reliable & scalable Data/ML pipelines for Analytics & AI/ML systems, working with large sets of structured and unstructured data from disparate sources
• Foundational acquaintance of Data Science & AI/ML models
• SQL, Python, Spark, PySpark
• Big Data systems - Hadoop Ecosystem (HDFS, Hive, MapReduce) or Cloud
• Analytics database like Druid, Data visualisation/exploration tools like Superset.
• Understanding of cloud platforms (AWS, Azure, or GCP)
• Version Control • GIT

Secondary Skills (desired/preferred)

• Apache Airflow, Apache Oozie, Nifi
• GCP cloud experience, Big Query, GCP Big Data Ecosystem.
• Trino/Presto
• Familiar with forecasting algorithms, such as Time Series (Arima, Prophet), ML (GLM, GBDT, XgBoost), Hierarchical model (Top Down, Bottom Up), DL (Seq2Seq, Transformer), and Ensemble methods.
• Domain experience on retail forecasting or any other business forecast predictions/time series forecasting
• Implement and manage continuous integration and continuous deployment (CI/CD) pipelines for Data Pipelines & AI/ML models
• Build and Maintain systems to power model experimentation, testing, and deployment phases.
• Manage end-to-end model lifecycle, including model registration, version control and deployment using tools like ML flow, Vertex AI etc.
• Familiar with pipeline, model monitoring to track performance drift, data quality and system health in production environments.
• MLOps tools and frameworks such as MLflow, Kubeflow or Vertex AI