About Job/Role

Partner with business, product, and engineering teams to define problem statements, evaluate feasibility, and design AI/ML-driven solutions that deliver measurable business value.
Lead and execute end-to-end AI/ML projects — from data exploration and model development to validation, deployment, and monitoring in production.
Drive solution architecture using techniques in data engineering, programming, machine learning, NLP, and Generative AI.
Champion the scalability, reproducibility, and sustainability of AI solutions by establishing best practices in model development, CI/CD, and performance tracking.
Guide junior and associate AI/ML engineers through technical mentoring, code reviews, and solution reviews.
Identify and evangelize the adoption of emerging tools, technologies, and methodologies across teams.
Translate technical outputs into actionable insights for business stakeholders through storytelling, data visualizations, and stakeholder engagement.

Roles and Responsibilities

Partner with business, product, and engineering teams to define problem statements, evaluate feasibility, and design AI/ML-driven solutions that deliver measurable business value.
Lead and execute end-to-end AI/ML projects — from data exploration and model development to validation, deployment, and monitoring in production.
Drive solution architecture using techniques in data engineering, programming, machine learning, NLP, and Generative AI.
Champion the scalability, reproducibility, and sustainability of AI solutions by establishing best practices in model development, CI/CD, and performance tracking.
Guide junior and associate AI/ML engineers through technical mentoring, code reviews, and solution reviews.
Identify and evangelize the adoption of emerging tools, technologies, and methodologies across teams.
Translate technical outputs into actionable insights for business stakeholders through storytelling, data visualizations, and stakeholder engagement.

Required Qualification

A seasoned AI/ML engineer with 7+ years of hands-on experience delivering enterprise-grade AI/ML solutions.
Advanced proficiency in Python, SQL, PySpark, and experience working with cloud platforms (Azure preferred) and tools such as Databricks, Synapse, ADF, and Web Apps.
Strong expertise in applied text analytics, NLP, and Generative AI, with real-world deployment exposure.
Solid understanding of model evaluation, optimization, bias mitigation, and monitoring in production.
A problem solver with scientific rigor, strong business acumen, and the ability to bridge the gap between data and decisions.
Prior experience in leading cross-functional AI initiatives or collaborating with engineering teams to deploy ML pipelines.
Bachelor’s or master’s degree in Computer Science, Engineering, Statistics, or a related quantitative field.
A PhD is a plus.
Prior understanding in business domain of shipping and logistics is an advantage.

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