AI​/ML Engineer Lead

Experience: 8+ years (with 3+ years in AI/ML project leadership)

Employment Type: Full-Time

Ibexlabs is an AWS Advanced Tier Consulting Partner with multiple competencies, including Security, Dev Ops, Healthcare, and Managed Services. Our team of dedicated and highly skilled engineers is passionate about helping customers accelerate their cloud transformation while ensuring security and compliance with industry best practices. As a rapidly growing company, we are seeking talented individuals to join us and contribute to our continued success.

We are seeking an experienced AI/ML Engineer Lead to design, develop, and deploy machine learning solutions that power intelligent decision-making across our products and platforms. The ideal candidate will combine strong technical expertise in data science, ML engineering, and AI model deployment with leadership experience guiding cross-functional teams toward impactful business outcomes.

• Lead the design, development, and implementation of end-to-end AI/ML solutions — from data collection and preprocessing to model deployment and monitoring.
• Collaborate with product managers, data engineers, and business stakeholders to identify AI opportunities and define technical roadmaps.
• Build, train, and optimize machine learning and deep learning models using state-of-the-art algorithms and frameworks.
• Architect and maintain scalable ML pipelines using modern MLOps practices.
• Evaluate, fine-tune, and product ionize models ensuring high performance, accuracy, and reliability.
• Mentor and guide a team of data scientists and ML engineers, driving best practices in model development and deployment.
• Stay current with emerging AI research, technologies, and tools to recommend strategic adoption.
• Establish and enforce standards for model governance, documentation, reproducibility, and compliance.

• Strong programming skills in Python (Num Py, Pandas, Scikit-learn, Tensor Flow, PyTorch).
• Deep understanding of machine learning, deep learning, NLP, and computer vision techniques.
• Experience in MLOps tools and frameworks such as MLflow, Kubeflow, Airflow, or Sage Maker.
• Solid understanding of data pipelines, feature stores, and model lifecycle management.
• Strong grasp of statistics, data analysis, and algorithm optimization.
• Experience integrating AI models with APIs or applications for production use.
• Proven leadership experience — mentoring engineers, conducting design reviews, and driving architectural decisions.
• Excellent analytical, problem-solving, and communication skills.