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Key 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.

- Effectively manage 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 advanced techniques in machine learning, NLP, Generative AI, and statistical modeling.

- 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.

We are looking for:

- Having minimum 1-2 years of experience in managing a Team of 5-6 AIML Engineers with effective communication and good story telling abilities.

- A seasoned AI/ML Engineering expert 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 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.