Dot Ai is not just another AI companywere a post-IPO force redefining the infrastructure that moves the world. By merging IoT hardware, real-time data, and intelligent machine learning pipelines, we deliver visibility, predictability, and efficiency to asset-heavy industries that havent seen real innovation in decades.

Now were scaling. Fast. And were looking for a Machine Learning Manager to lead the team building the models at the heart of our platform.

The Opportunity : ML Engineer at Dot Ai

This is not an ivory tower research role. At Dot Ai, our ML is applied, operational, and deeply embedded in the products that power global logistics. As ML Manager, youll lead a growing team of engineers and data scientists, working at the intersection of experimentation and production, building scalable models that inform critical business decisions, automate operations, and drive predictive insight at scale.

Youll define the bar for machine learning at Dot Aiand then raise it.

What Youll Be Doing :

- Lead, mentor, and grow a world-class team of ML engineers and data scientists

- Drive full lifecycle development of ML models from exploration and prototyping to deployment, monitoring, and retraining

- Translate business and product goals into ML solutions that solve real customer problems

- Architect model pipelines, design features, evaluate performance, and enforce reproducibility

- Collaborate across engineering, product, and design to ship production-grade ML systems that scale

- Champion responsible AI : ensure fairness, transparency, and explainability in every deployment

- Optimize and evolve our ML infrastructure, CI/CD, observability, model versioning, A/B testing, and retraining workflows

- Stay sharp on the latest in AI/ML research and apply relevant advances in LLMs, vision, and generative models to our roadmap

What You Bring :

- Bachelor's or Masters in Computer Science, AI, Machine Learning, or a related field (PhD a plus)

- 3+ years of experience in machine learning or applied data science, with 1-2 years in a leadership or tech lead role

- Advanced proficiency in Python and frameworks like TensorFlow, PyTorch, and scikit-learn

- Experience deploying ML models in production using Docker, Kubernetes, and cloud environments (AWS, GCP, or Azure)

- Familiarity with APIs, data pipelines, and MLOps tooling

- Proven ability to mentor technical talent, drive delivery, and balance experimentation with execution

- Strong communication skills and comfort working cross-functionally in a fast-paced startup environment

Bonus Points For :

- Experience working in early-stage or high-growth tech environments

- Background in LLMs, generative AI, or applied research using OpenAI, Hugging Face, etc.

- Domain experience in NLP, computer vision, or reinforcement learning

- Hands-on with ML observability and monitoring platforms

Why Dot Ai :

Because youre not looking to join the machine. You want to build it. This is a rare opportunity to shape how a public AI company applies machine learning at global scale, in real-world logistics environments where precision, impact, and performance matter.

If you're ready to move fast, lead boldly, and ship models that make a measurable differencewelcome to the foundational team.