AI/ML Engineer

Responsibilities

• Demonstrates proficiency in designing, developing, and deploying machine learning models (e.g., regression, classification, ensemble methods) to address complex analytical problems.
• Represents the team in cross-functional engagements with business, engineering, and analytics stakeholders, providing technical leadership in AI solution design and implementation.
• Applies extensive technical knowledge to develop and maintain scalable data pipelines and ML workflows across modern data platforms (e.g., cloud-based environments, distributed processing systems).
• Applies organizational and third-party technologies to build complex AI-driven solutions, independently implementing end-to-end pipelines from data ingestion to deployment.
• Integrates technical expertise with business understanding to deliver impactful insights, collaborating with stakeholders to translate model outputs into actionable outcomes.
• Designs, develops, tests, and deploys data models, feature pipelines, and scoring systems ensuring performance, reliability, and scalability.
• Develops standards, reusable templates, and best practices for model development, feature engineering, and evaluation to ensure consistency and governance.
• Defines scope, plans, and deliverables for assigned components, ensuring alignment with project objectives and timelines.
• Applies advanced subject matter knowledge, contributes to complex projects, and exercises independent judgment in resolving business issues and optimizing solutions.
• Builds strong internal and external working relationships and provides mentoring and guidance to junior team members.
• Education & Experience Recommended
• Four-year or Graduate Degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or any related discipline; or equivalent work experience.
• Typically has 5-10 years of experience in machine learning, data science, or software engineering roles, preferably in large-scale or enterprise environments.
• Preferred Certifications
• Microsoft Azure AI Engineer Associate / Data Scientist Associate (preferred)
• Databricks or equivalent platform certifications (good to have)
• Knowledge & Skills
• Agile Methodology
• Application Development
• Machine Learning (Supervised & Unsupervised)
• Feature Engineering & Model Optimization
• Model Evaluation (Accuracy, Precision, Recall, F1 Score, ROC-AUC)
• Python (Programming Language)
• SQL (Programming Language)
• Distributed Computing (e.g., PySpark or similar)
• Data Engineering & ETL Pipelines
• API Development & Integration
• Automation
• Business Process & Requirements Analysis
• Debugging & Performance Optimization
• Cloud Platforms (e.g., Azure, AWS, GCP)
• Data Visualization (e.g., Power BI or similar tools)
• Software Development Lifecycle (SDLC)
• Cross-Org Skills
• Effective Communication
• Results Orientation
• Learning Agility
• Digital Fluency
• Customer Centricity
• Impact & Scope
• Impacts functional and cross-functional teams by contributing technical expertise to AI/ML initiatives and supporting enterprise-scale analytics solutions.
• Complexity
• Works on complex problems where analysis of situations or data requires an in-depth evaluation of multiple factors, including technical feasibility, scalability, and business impact.
• Sales&Services entity

Benefits

Additional Information

AI/ML Engineer Description - Job Summary - This role is responsible for designing and developing advanced AI/ML solutions to solve complex business problems. The role applies deep technical expertise to build scalable models, data pipelines, and intelligent systems, while ensuring consistency, quality, and alignment with enterprise standards. The role contributes to complex initiatives, collaborates across global teams, and mentors junior team members to drive adoption of data-driven solutions.

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Company Intel

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