AI Engineer
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AI Engineer
Location
Bangalore RMZ-ECO WORLD
Experience
Senior
Posted
Jul 7, 2026
Apply by
July 16, 2026
Applicants
0
Early applicantFull-timeWork from Office
Job Description
, India
**Job Family Group:**
Research and Development
**Worker Type:**
Regular
**Posting Start Date:**
July 6, 2026
**Business Unit:**
Information & Digital Technology
**Experience Level:**
Experienced Professionals
**Job Description:**
**Job Description:**
Data and Software Engineering in Data Science and Machine Learning drives business value through providing quality technical, functional and consulting expertise to deliver the right skills, at the right time, in the right place. In DSE Engineering you will have opportunities to work on E2E programs and products across the value chain of Shell.
- Create full-stack data science application and tools on a digital platform
- Responsible for delivery of data science tasks for a product in a production scale environment through Agile
- Understand the product lifecycle especially relating to data science, development to support
- Follow discipline maturation initiatives; contribute to InnerSource
- Deepen knowledge of current and emerging AI Engineering practices and technologies and gain applicable certifications
**Skills & Requirements:**
- Bachelor or Master’s degree in quantitative subjects like Data Science, Computer Science, Applied Mathematics, Statistics, Physics. Minimum 7 years of experience in the industry
- Practical experience in developing end-to-end models using machine learning for predictive modelling in a business/industry environment, i.e., feature engineering, model creation, evaluation and postproduction support mechanisms
- Hands-on experience in building large scale distributed Machine Learning Applications using microservices and event driven systems-based practices
- Extensive experience in designing applications with Azure Machine Learning Services
- Technical Knowledge of MLOps principles and standards to build ML pipelines for automated model deployment, model performance monitoring, data drift detection in market standard platforms like Azure Machine Learning, AWS Sagemaker or Databricks.
- Strong interest and curiosity in exploring a wide range of languages, frameworks, and tools, including Python, PySpark, .NET/C#, Java, JavaScript, Kubernetes, and Kafka
- Experience in extracting, cleansing, and manipulating large, diverse structured and unstructured data sets and designing workflow or Orchestration systems such as ADF, Airflow, Databricks, Dagster, Datalake etc
- Skilled in at least one of the following:
- GenAI, LLM models, ML algorithms, Machine Vision, NLP
- Cloud Application development, deployment, and monitoring on platforms like Azure, AWS
- Deep knowledge of the technology landscape and context in one or more Shell core business areas, e.g. SSW, IGUPT, RES, etc
- Passionate and experienced in working with small, empowered, cross-functional teams focused on delivery. Possesses strong interpersonal skills for both teamwork and independent work, and is adept at collaborating with virtual teams and stakeholders in agile environments
-
**DISCLAIMER:**
Please note: We occasionally amend or withdraw Shell jobs and reserve the right to do so at any time, including prior to the advertised closing date. Before applying, you are advised to read our data protection policy. This policy describes the processing that may be associated with your personal data and informs you that your personal data may be transferred to Shell/Shell Group companies around the world. The Shell Group and its approved recruitment consultants will never ask you for a fee to process or consider your application for a career with Shell. Anyone who demands such a fee is not an authorised Shell representative and you are strongly advised to refuse any such demand. Shell is an Equal Opportunity Employer.
Key Responsibilities
- Create full-stack data science applications and tools on a digital platform
- Deliver data science tasks for products in production-scale environments using Agile
- Understand product lifecycle, particularly regarding data science and development support
- Contribute to discipline maturation initiatives and InnerSource
- Deepen knowledge of AI Engineering practices and technologies
- Gain applicable certifications
Requirements
- Bachelor's or Master's degree in quantitative subjects such as Data Science
- Computer Science
- Applied Mathematics
- Statistics
- or Physics
Skills Required
Machine LearningPredictive ModellingFeature EngineeringModel CreationModel EvaluationPostproduction SupportDistributed Machine LearningMicroservicesEvent Driven SystemsAzure Machine Learning ServicesMLOpsModel DeploymentModel Performance MonitoringData Drift DetectionPythonPySpark.NET/C#JavaJavaScriptKubernetesKafkaData ExtractionData CleansingData ManipulationWorkflow OrchestrationADFAirflowDatabricksDagsterDatalakeGenAILLM ModelsMachine VisionNLPCloud Application DevelopmentAzureAWSInterpersonal SkillsTeamworkIndependent WorkCollaborationAgile Mindset
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