Engineer, Data Science

Overview

Applied Data Science role within highly automated manufacturing environments, building machine learning, Generative AI and Agentic AI solutions. This is an applied position rather than a research role.

What you'll do

• Build data science, machine learning, Generative AI and Agentic AI solutions within highly automated manufacturing environments.
• Extract and integrate data from multiple sources using SQL, APIs, ETL/ELT pipelines and other query mechanisms.
• Cleanse data and perform feature extraction, outlier detection, missing-data handling, data quality checks and data transformation.
• Translate complex business and manufacturing problems into scalable data and AI solutions.
• Communicate technical findings effectively to both technical and business stakeholders.

What you'll need

• Strong interest in building a career in Data Science, Machine Learning, Generative AI, and Agentic AI.
• Hands-on experience or strong knowledge in Agentic AI, machine learning, statistical modeling, feature engineering, exploratory data analysis, and supervised, unsupervised and semi-supervised learning.
• Strong proficiency in Python and/or R, with solid software development and scripting capabilities.
• Experience working with SQL databases and large-scale data platforms, including Snowflake, Teradata, or similar technologies.
• Knowledge of the Snowflake ecosystem, including data transformation, analytical workloads, and integration of Snowflake data with Python/ML applications.
• Strong understanding of data cleansing, feature extraction, outlier detection, missing-data handling, data quality, and data transformation techniques.
• Experience with distributed data processing technologies such as PySpark, Apache Spark, SparkR, or SparklyR.
• Experience with TensorFlow, PyTorch, scikit-learn, or other machine learning/statistical frameworks.
• Familiarity with SSIS, ETL/ELT processes, data pipelines, and data integration patterns.
• Strong software engineering fundamentals, including writing maintainable, reusable, production-quality code and working with version-control practices.
• Strong analytical and problem-solving skills.
• Strong verbal and written communication skills.

Nice to have

• Experience with Snowpark, Snowflake Cortex AI, or similar AI/ML capabilities.
• Experience with Microsoft Azure technologies, particularly services used for data, analytics, AI, and application deployment.
• Exposure to Azure Data Factory, Azure Databricks, Azure Machine Learning, Azure OpenAI, ADLS, or related Azure services.
• Experience working with time-series data, image data, semi-supervised learning, anomaly detection, and datasets with frequently changing distributions.
• Exposure to visualization or application technologies such as Tableau, Power BI, JavaScript, or Angular.
• Experience working with Manufacturing Execution Systems (MES) or semiconductor/manufacturing datasets.
• Experience with Generative AI, RAG, AI agents, LLM-based applications, prompt engineering, or enterprise AI solutions.
• Publications at conferences such as CVPR, NeurIPS, ICML, or KDD.

Details

• Location: Hyderabad - Phoenix Aquila, India.