Lead AI Engineer
IBM
Lead AI Engineer
Job Description
Lead AI Engineer
📋 Job Overview
The Lead AI Engineer at IBM will spearhead the integration of Large Language Models (LLMs) into IBM's Automation product portfolio. This role involves leading data collection efforts for LLM training, designing robust data pipelines, and establishing best practices for AI/ML feature implementation across product teams.
📍 Location: Krakow, PL (Remote/Hybrid)
💼 Career Level: Professional
🎯 Key Responsibilities
- Lead design and implementation of data collection pipelines for LLM training datasets
- Develop data quality assessment frameworks
- Create annotation guidelines and workflows for domain-specific datasets
- Implement data governance protocols ensuring compliance with privacy and ethical AI principles
- Establish evaluation datasets and benchmarks for LLM performance
- Architect solutions to integrate LLMs with IBM's products and ecosystem
- Develop APIs and interfaces for LLM interaction with other software components
- Optimize LLM deployment across various computing environments
- Implement model compression, quantization, and optimization techniques
- Design and implement prompt engineering frameworks
- Establish technical standards and best practices for AI/ML feature implementation
- Create reusable components and design patterns for LLM use cases
- Develop monitoring systems for model performance, drift, and biases
- Research and implement techniques for responsible AI
- Collaborate with product teams to identify AI-driven innovation opportunities
✅ Required Qualifications
- Experience in AI/ML engineering, specializing in Large Language Models (LLMs)
- Proven track record in leading data collection and management for LLM training and evaluation
- Expertise in integrating LLM technologies into existing and new products
⭐ Preferred Qualifications
- Experience with IBM AI Model & Data Catalog
- Knowledge of FM-Eval and Unitxt for LLM performance evaluation
- Familiarity with IBM Data & Model Governance process and tooling
🛠️ Required Skills
- AI/ML engineering
- Large Language Models (LLMs)
- Data collection and management
- Data pipeline design
- Data quality assessment
- Annotation guidelines creation
- Data governance
- Privacy compliance
- Ethical AI principles
- Evaluation datasets and benchmarks
- API development
- Interface design
- Deployment optimization
- Model compression
- Quantization
- Prompt engineering
- Technical standards
- Best practices
- Reusable components
- Design patterns
- Monitoring systems
- Responsible AI
- Explainability
- Fairness
- Collaboration
- Innovation
🎁 Benefits & Perks
- Opportunity for learning and career development
- Encouragement to be courageous and experiment
- Continuous trust and support in a thriving environment
- Growth-minded culture with openness to feedback and learning
- Collaborative team-focused approach
- Equal-opportunity employment
Locations
- Krakow, PL, India (Remote)
Salary
Estimated Salary Rangemedium confidence
2,500,000 - 4,200,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- AI/ML engineeringintermediate
- Large Language Models (LLMs)intermediate
- Data collection and managementintermediate
- Data pipeline designintermediate
- Data quality assessmentintermediate
- Annotation guidelines creationintermediate
- Data governanceintermediate
- Privacy complianceintermediate
- Ethical AI principlesintermediate
- Evaluation datasets and benchmarksintermediate
- API developmentintermediate
- Interface designintermediate
- Deployment optimizationintermediate
- Model compressionintermediate
- Quantizationintermediate
- Prompt engineeringintermediate
- Technical standardsintermediate
- Best practicesintermediate
- Reusable componentsintermediate
- Design patternsintermediate
- Monitoring systemsintermediate
- Responsible AIintermediate
- Explainabilityintermediate
- Fairnessintermediate
- Collaborationintermediate
- Innovationintermediate
Required Qualifications
- Experience in AI/ML engineering, specializing in Large Language Models (LLMs) (experience)
- Proven track record in leading data collection and management for LLM training and evaluation (experience)
- Expertise in integrating LLM technologies into existing and new products (experience)
Preferred Qualifications
- Experience with IBM AI Model & Data Catalog (experience)
- Knowledge of FM-Eval and Unitxt for LLM performance evaluation (experience)
- Familiarity with IBM Data & Model Governance process and tooling (experience)
Responsibilities
- Lead design and implementation of data collection pipelines for LLM training datasets
- Develop data quality assessment frameworks
- Create annotation guidelines and workflows for domain-specific datasets
- Implement data governance protocols ensuring compliance with privacy and ethical AI principles
- Establish evaluation datasets and benchmarks for LLM performance
- Architect solutions to integrate LLMs with IBM's products and ecosystem
- Develop APIs and interfaces for LLM interaction with other software components
- Optimize LLM deployment across various computing environments
- Implement model compression, quantization, and optimization techniques
- Design and implement prompt engineering frameworks
- Establish technical standards and best practices for AI/ML feature implementation
- Create reusable components and design patterns for LLM use cases
- Develop monitoring systems for model performance, drift, and biases
- Research and implement techniques for responsible AI
- Collaborate with product teams to identify AI-driven innovation opportunities
Benefits
- general: Opportunity for learning and career development
- general: Encouragement to be courageous and experiment
- general: Continuous trust and support in a thriving environment
- general: Growth-minded culture with openness to feedback and learning
- general: Collaborative team-focused approach
- general: Equal-opportunity employment
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Lead AI Engineer
IBM
Lead AI Engineer
Job Description
Lead AI Engineer
📋 Job Overview
The Lead AI Engineer at IBM will spearhead the integration of Large Language Models (LLMs) into IBM's Automation product portfolio. This role involves leading data collection efforts for LLM training, designing robust data pipelines, and establishing best practices for AI/ML feature implementation across product teams.
📍 Location: Krakow, PL (Remote/Hybrid)
💼 Career Level: Professional
🎯 Key Responsibilities
- Lead design and implementation of data collection pipelines for LLM training datasets
- Develop data quality assessment frameworks
- Create annotation guidelines and workflows for domain-specific datasets
- Implement data governance protocols ensuring compliance with privacy and ethical AI principles
- Establish evaluation datasets and benchmarks for LLM performance
- Architect solutions to integrate LLMs with IBM's products and ecosystem
- Develop APIs and interfaces for LLM interaction with other software components
- Optimize LLM deployment across various computing environments
- Implement model compression, quantization, and optimization techniques
- Design and implement prompt engineering frameworks
- Establish technical standards and best practices for AI/ML feature implementation
- Create reusable components and design patterns for LLM use cases
- Develop monitoring systems for model performance, drift, and biases
- Research and implement techniques for responsible AI
- Collaborate with product teams to identify AI-driven innovation opportunities
✅ Required Qualifications
- Experience in AI/ML engineering, specializing in Large Language Models (LLMs)
- Proven track record in leading data collection and management for LLM training and evaluation
- Expertise in integrating LLM technologies into existing and new products
⭐ Preferred Qualifications
- Experience with IBM AI Model & Data Catalog
- Knowledge of FM-Eval and Unitxt for LLM performance evaluation
- Familiarity with IBM Data & Model Governance process and tooling
🛠️ Required Skills
- AI/ML engineering
- Large Language Models (LLMs)
- Data collection and management
- Data pipeline design
- Data quality assessment
- Annotation guidelines creation
- Data governance
- Privacy compliance
- Ethical AI principles
- Evaluation datasets and benchmarks
- API development
- Interface design
- Deployment optimization
- Model compression
- Quantization
- Prompt engineering
- Technical standards
- Best practices
- Reusable components
- Design patterns
- Monitoring systems
- Responsible AI
- Explainability
- Fairness
- Collaboration
- Innovation
🎁 Benefits & Perks
- Opportunity for learning and career development
- Encouragement to be courageous and experiment
- Continuous trust and support in a thriving environment
- Growth-minded culture with openness to feedback and learning
- Collaborative team-focused approach
- Equal-opportunity employment
Locations
- Krakow, PL, India (Remote)
Salary
Estimated Salary Rangemedium confidence
2,500,000 - 4,200,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- AI/ML engineeringintermediate
- Large Language Models (LLMs)intermediate
- Data collection and managementintermediate
- Data pipeline designintermediate
- Data quality assessmentintermediate
- Annotation guidelines creationintermediate
- Data governanceintermediate
- Privacy complianceintermediate
- Ethical AI principlesintermediate
- Evaluation datasets and benchmarksintermediate
- API developmentintermediate
- Interface designintermediate
- Deployment optimizationintermediate
- Model compressionintermediate
- Quantizationintermediate
- Prompt engineeringintermediate
- Technical standardsintermediate
- Best practicesintermediate
- Reusable componentsintermediate
- Design patternsintermediate
- Monitoring systemsintermediate
- Responsible AIintermediate
- Explainabilityintermediate
- Fairnessintermediate
- Collaborationintermediate
- Innovationintermediate
Required Qualifications
- Experience in AI/ML engineering, specializing in Large Language Models (LLMs) (experience)
- Proven track record in leading data collection and management for LLM training and evaluation (experience)
- Expertise in integrating LLM technologies into existing and new products (experience)
Preferred Qualifications
- Experience with IBM AI Model & Data Catalog (experience)
- Knowledge of FM-Eval and Unitxt for LLM performance evaluation (experience)
- Familiarity with IBM Data & Model Governance process and tooling (experience)
Responsibilities
- Lead design and implementation of data collection pipelines for LLM training datasets
- Develop data quality assessment frameworks
- Create annotation guidelines and workflows for domain-specific datasets
- Implement data governance protocols ensuring compliance with privacy and ethical AI principles
- Establish evaluation datasets and benchmarks for LLM performance
- Architect solutions to integrate LLMs with IBM's products and ecosystem
- Develop APIs and interfaces for LLM interaction with other software components
- Optimize LLM deployment across various computing environments
- Implement model compression, quantization, and optimization techniques
- Design and implement prompt engineering frameworks
- Establish technical standards and best practices for AI/ML feature implementation
- Create reusable components and design patterns for LLM use cases
- Develop monitoring systems for model performance, drift, and biases
- Research and implement techniques for responsible AI
- Collaborate with product teams to identify AI-driven innovation opportunities
Benefits
- general: Opportunity for learning and career development
- general: Encouragement to be courageous and experiment
- general: Continuous trust and support in a thriving environment
- general: Growth-minded culture with openness to feedback and learning
- general: Collaborative team-focused approach
- general: Equal-opportunity employment
Tags & Categories
Answer 10 quick questions to check your fit for Lead AI Engineer @ IBM.
10 Questions
~2 Minutes
Instant Score
Related Books and Jobs