AI/ML Engineer

Role Overview

Seeking a senior AI/ML Engineer with 8+ years of experience to design and deliver scalable machine learning systems in production. The role owns end-to-end architecture from data pipelines and training to lowlatency serving, monitoring, and iteration. You will apply advanced statistical modeling to solve complex business problems, ensure robust evaluation, and drive measurable impact. The position also explores and operationalizes cuttingedge approaches such as Transformers and LLMs where they add clear value. You will influence AI strategy, mentor teams, and establish best practices for reliability, performance, and cost efficiency.

Required Qualifications

• 8+ years of professional experience in AI/ML engineering or closely related roles
• Proven track record designing and operating scalable ML systems in production (training, serving, monitoring)
• Expertise in advanced statistical modeling (e.g., Bayesian methods, GLMs, time series, causal inference)
• Hands-on experience with modern deep learning frameworks for Transformers/LLMs (e.g., Hugging Face Transformers with PyTorch or TensorFlow)
• Experience leading or influencing AI strategy, technical roadmaps, and stakeholder alignment
• Strong background in data pipelines and feature engineering for large-scale ML
• Experience with experiment design, offline/online evaluation, and A/B testing at scale

Responsibilities

• Architect end-to-end, scalable ML solutions from data ingestion and feature engineering to training, deployment, and serving
• Build, productionize, and operate ML models with strong SLAs, observability, and cost/performance targets
• Apply advanced statistical modeling techniques to improve model reliability, interpretability, and business impact
• Evaluate, adopt, and operationalize modern frameworks including Transformers and LLMs when appropriate
• Lead or influence AI strategy, collaborate with product and engineering, and mentor team members
• Define standards for model governance, versioning, monitoring, and drift management
• Design and run experiments (A/B tests), report results, and iterate based on evidence