AI/ML Engineer

Looking for a skilled AI/ML Engineer to develop and enhance purchasing processes through advanced data analysis, deep learning models, and supplier-focused functional innovations, while collaborating with stakeholders to solve business challenges efficiently.

Responsibilities

 

• Responsible for developing AI related enhancements for Purchasing PDO team and proficient in managing supplier related functional enhancements infusing AI to the processes.
• Collect, clean, and preprocess large and complex datasets from various sources.
• Applying various Deep learning networks, statistical techniques, explore and experiment on new models through research papers or via various frameworks.
• Understanding, transforming large scale data to usable form for modelling, filtering data with generalization for later use, Cross-validating models for the requirements.
• Interact with internal stakeholders to understand the business problems and automate / solve widely varying Purchasing business needs within 1-2 weeks from beginning of requirement to delivery.
• Recommend and justify the algorithms to implement for the problems at-hand.
• Enhance deep learning networks with multi-GPU and multi-node capabilities.
• Supplier relationship framework assessment and build a survey to integrate with client .
• Perform exploratory data analysis (EDA) to understand data characteristics, identify patterns, and formulate hypotheses.
• Design and execute A/B tests or other experimental designs to evaluate the impact of new features or strategies.
• Monitor model performance in production and iterate on models to improve accuracy and efficiency.
• Stay up to date with the latest research and developments in data science, machine learning, and related fields, and evaluate their potential application.
• Help IT teams to develop a quick proof-of-concept to validate the concept and establish feasibility
• Experience Required
  
   
• 4+ years of experience working as a Data Scientist or in a similar role.
• Strong proficiency in at least one major programming language used in data science (Python, Java, R).
• Proven experience in developing and implementing solutions using Large Language Models (LLMs) and core Machine Learning techniques.
• Solid experience with data manipulation and analysis libraries (e.g., pandas, NumPy in Python; dplyr, data.table in R).
• Expertise in SQL for querying and manipulating databases.
• Demonstrated experience developing and applying various machine learning algorithms (e.g., regression, classification, clustering, tree-based methods, ensemble methods). Understanding of statistical concepts and their application (hypothesis testing, confidence intervals, experimental design).
• Experience with data visualization tools and libraries (e.g., Matplotlib, Seaborn, Plotly in Python; ggplot2 in R; Tableau, Power BI).
  
   

Experience Preferred

 

• Experience with big data technologies (e.g., Spark, Hadoop, Hive).
• Familiarity with cloud computing platforms (e.g., AWS, Azure, GCP) and their data/ML services.
• Experience with deep learning frameworks (e.g., TensorFlow, PyTorch, Keras).
• Experience deploying machine learning models into production environments.
• Knowledge of Automotive supply chain process.
• Experience with MLOps practices and tools.
• Contributions to open-source projects or publications in relevant fields.
  
   

Education Required:

 

• Bachelor's, Master's, in a quantitative field such as Computer Science, Statistics, Mathematics, or a related discipline