Artificial Intelligence Engineer

Job Scope

Research, design, and development of advanced AI and ML models powering a cuttingedge AI-driven no-code development platform and a scalable AI inference and training orchestration system. Responsible for building scalable ML pipelines, optimizing models for production, mentoring team members, and translating research innovations into impactful product features aligned with business goals.

Total /Relevant Experience

Five plus experience with AI-driven no-code platforms or automated code generation.

Key Responsibilities

Design and implement state-of-the-art machine learning and deep learning models for NLP, computer vision, and generative AI relevant to no-code AI coding and AI orchestration platforms.
Develop, optimize, and fine-tune large-scale models, including transformer-based architectures and generative models.
Architect and manage end-to-end machine learning pipelines: data processing, training, evaluation, deployment, and continuous monitoring.
Collaborate closely with software engineering teams to productionize models ensuring reliability, scalability, and performance.
Research and integrate cutting-edge AI techniques and algorithms to maintain product competitiveness.
Contributing to intellectual property generation, patents, and academic publications.
Provide technical leadership and mentorship to junior AI/ML team members.
Collaborate cross-functionally with product managers, UX designers, and engineers to deliver AI-powered product features.
Maintain up-to-date knowledge of AI research trends and technologies, assessing their applicability.
Ensure compliance with data privacy and security standards in AI model development.

Must-have skill

Experience with AI-driven no-code platforms or automated code generation.
Familiarity with AI workflow orchestration frameworks like LangChain, Crew AI, or similar.
Knowledge of probabilistic modeling and uncertainty quantification.
Hands-on experience with MLOps tools and practices including CI/CD, model versioning, and monitoring.

Good-to-Have Skills

Familiarity with cloud platforms (AWS, GCP, Azure) and container orchestration (Docker, Kubernetes).
Contributions to open-source AI projects or patent filings. Understanding of AI ethics, data privacy (GDPR, SOC2) compliance.
Strong academic research background with publications in top-tier AI/ML conferences.

Qualifications Criteria

Bachelor's in Computer Science, Electrical Engineering, Statistics, Mathematics, or related fields with a specialization in Artificial Intelligence, Machine Learning, or Deep Learning.

Strong research publication record in reputed AI/ML conferences (NeurIPS, ICML, ICLR, CVPR, ACL).
Demonstrated experience in developing and deploying deep learning models including transformers, CNNs, RNNs, GNNs, and generative AI models.