Job
Description
Education: Bachelorâs or masterâs in computer science, Software Engineering, or a related field (or equivalent practical experience). Hands-On ML/AI Experience: Proven record of deploying, fine-tuning, or integrating large-scale NLP models or other advanced ML solutions. Programming & Frameworks: Strong proficiency in Python (PyTorch or TensorFlow) and familiarity with MLOps tools (e.g., Airflow, MLflow, Docker). Security & Compliance: Understanding of data privacy frameworks, encryption, and secure data handling practices, especially for sensitive internal documents. DevOps Knowledge: Comfortable setting up continuous integration/continuous delivery (CI/CD) pipelines, container orchestration (Kubernetes), and version control (Git). Collaborative Mindset: Experience working cross-functionally with technical and non-technical teams; ability to clearly communicate complex AI concepts. Role Overview Collaborate with cross-functional teams to build AI-driven applications for improved productivity and reporting. Lead integrations with hosted AI solutions (ChatGPT, Claude, Grok) for immediate functionality without transmitting sensitive data while laying the groundwork for a robust in-house AI infrastructure. Develop and maintain on-premises large language model (LLM) solutions (e.g. Llama) to ensure data privacy and secure intellectual property. Key Responsibilities LLM Pipeline Ownership: Set up, fine-tune, and deploy on-prem LLMs; manage data ingestion, cleaning, and maintenance for domain-specific knowledge bases. Data Governance & Security: Assist our IT department to implement role-based access controls, encryption protocols, and best practices to protect sensitive engineering data. Infrastructure & Tooling: Oversee hardware/server configurations (or cloud alternatives) for AI workloads; evaluate resource usage and optimize model performance. Software Development: Build and maintain internal AI-driven applications and services (e.g., automated report generation, advanced analytics, RAG interfaces, as well as custom desktop applications). Integration & Automation: Collaborate with project managers and domain experts to automate routine deliverables (reports, proposals, calculations) and speed up existing workflows. Best Practices & Documentation: Define coding standards, maintain technical documentation, and champion CI/CD and DevOps practices for AI software. Team Support & Training: Provide guidance to data analysts and junior developers on AI tool usage, ensuring alignment with internal policies and limiting model âhallucinations.â Performance Monitoring: Track AI system metrics (speed, accuracy, utilization) and implement updates or retraining as necessary. Job Types: Full-time, Permanent Pay: âč80,000.00 - âč90,000.00 per month Benefits: Health insurance Provident Fund Schedule: Day shift Monday to Friday Supplemental Pay: Yearly bonus Work Location: In person Application Deadline: 30/06/2025 Expected Start Date: 30/06/2025
