Key skills
PythonAI technologiesAI/ML algorithmsCloud platformsData analytics toolsData engineeringcommunicationProblem-solvingAttention to detailSQLAIMachine LearningMLNLPNatural Language ProcessingComputer VisionLangChainData EngineeringAnalyticsSparkHadoopAWSAzureGCPGoogle CloudGitHubGitLabBitbucketVersion ControlPerformance OptimizationAgileScrumCommunicationProblem SolvingCollaboration
About this role
IBM is a leading technology company that seeks to solve some of the world's most challenging problems. The Consultant - AI Engineering role involves developing and training AI tools, collaborating with clients to design and implement AI solutions, and ensuring the integration of these technologies into business processes.
Responsibilities:
- AI Solution Design: Collaborate with cross-functional teams to design AI models and algorithms that solve business problems for clients
- Model Development: Build, train, and deploy machine learning models, natural language processing systems, and computer vision applications
- Client Engagement: Understand client requirements, present AI solutions, and work with clients to integrate AI technologies into their business processes
- Data Preprocessing: Clean, analyze, and prepare large datasets for machine learning and AI model training
- Implementation & Deployment: Implement AI solutions and ensure smooth deployment on cloud-based environments, ensuring scalability and performance optimization
- Cloud Management Strategies: Oversee and maintain a deep understanding of various services like AWS, Azure, and GCP
- Collaborative Problem Solving: Work with software development and IT teams to integrate AI models into production systems and ensure their continuous improvement
- AI Research & Innovation: Stay ahead of industry trends and emerging technologies in AI and data science, and leverage this knowledge to drive innovation within the organization
- Documentation: Prepare detailed documentation for AI models, algorithms, and implementation processes to ensure knowledge transfer and scalability. Manage and enforce best practices for version control and collaboration tools, such as Github, Bitbucket, and Gitlab
Requirements:
- Bachelor's degree in Computer Science, Data Science, AI, or related field (Master's or Ph.D. is a plus)
- Minimum of 3-5 years of experience in AI engineering, machine learning, or related fields
- Experience working in a professional services or consulting environment is highly desirable
- Expert proficiency in Python, with experience in other programming languages highly valued
- Deep knowledge and practical implementation of advanced AI technologies, including Langchain, Vector Stores, etc
- Strong understanding of AI/ML algorithms (supervised/unsupervised learning, reinforcement learning)
- Familiarity with cloud platforms (AWS, Azure, Google Cloud) for deploying AI models
- Experience with data analytics and data engineering tools (SQL, Hadoop, Spark)
- Proven experience in planning, developing, and implementing complex data pipelines
- Strong communication skills with the ability to explain complex AI concepts to non-technical stakeholders
- Ability to work in a fast-paced, client-facing environment with attention to detail
- Strong problem-solving skills and the ability to think creatively to solve client challenges
- Knowledge of industry-specific AI applications (e.g., healthcare, financial services, supply chain, retail/CPG)
- Experience with natural language processing (NLP) and computer vision technologies
- Previous experience in an Agile or Scrum environment