AI/ML Engineer

AI/ML Engineer

This role is responsible for developing intelligent programs, AI-powered applications, and advanced algorithms to enable data-driven decision-making and automation. The position leverages modern AI techniques including deep learning, generative AI, natural language processing (NLP), computer vision, reinforcement learning, intelligent process automation, and virtual assistants.

Key responsibilities include:

• Translating business requirements into AI-driven solutions, including models, algorithms, and applications that solve complex problems, generate recommendations, detect patterns, and make predictions
• Developing data-driven applications that convert large-scale data into actionable insights through experimentation and advanced analytics
• Designing and implementing AI solutions across domains such as NLP, generative AI, image/sensor processing, cognitive automation, and intelligent process automation
• Optimizing and enhancing AI models and technologies to improve accuracy, scalability, and efficiency
• Partnering with supply chain and business stakeholders to gather requirements and ensure solutions deliver measurable business value
• Leading integration and deployment of AI models (internal and COTS) within cloud environments (primarily GCP)
• Collaborating with Knowledge Graph teams to align AI models with enterprise ontologies and enable advanced graph-based analytics
• Executing AI model inference using graph data to support supplier risk analysis and material movement optimization
• Championing AI-driven SDLC practices using tools such as GitHub Copilot, automated PR agents, and AI-generated documentation
• Designing and maintaining MLOps pipelines to ensure continuous integration of data and model updates
• Developing reusable integration patterns and data contracts to support scalability across business units

Required skills include:

• Artificial Intelligence & Expert Systems
• Machine Learning
• Data Science and Advanced Analytics
• Data Modeling
• Software Development Lifecycle (SDLC)

Required qualifications include:

• Bachelor's degree in Computer Science, Engineering, Data Science, or a related technical field
• 5+ years of experience in AI/ML, data science, or advanced analytics, delivering production-grade solutions in enterprise environments
• Strong proficiency in Python and SQL; familiarity with graph query languages (e.g., Cypher)
• Hands-on experience with MLOps tools and frameworks (e.g., Azure ML, AWS SageMaker, GCP Vertex AI, Kubeflow, MLflow)
• Strong expertise in cloud platforms (GCP preferred) and data integration architectures
• Proven ability to design and implement AI-specific SDLC frameworks
• Strong analytical, problem-solving, and critical thinking skills
• Excellent communication and stakeholder management capabilities

Preferred qualifications include:

• Experience leveraging AI tools to improve engineering productivity (e.g., agentic workflows, RAG-based solutions)
• Background in product engineering and requirements translation for AI implementations
• Understanding of knowledge graphs, semantic ontologies, and their application to analytics
• Experience integrating COTS AI solutions into enterprise environments
• Domain knowledge in supply chain operations, including demand planning, logistics, risk, sustainability, and resilience

Education:

• Required: Bachelor's Degree
• Preferred: Master's Degree

Additional information:

• Hybrid role – 4 days onsite
• Focus on building AI-driven decision support tools within supply chain environments
• Opportunity to work across AI model integration, knowledge graphs, and enterprise-scale MLOps frameworks