The opportunity
We challenge the status quo because we know a better supply chain isn’t just possible—it’s essential. Better for our customers.
What you'll do
Staff ML Engineerto lead the development of next-generation AI/ML systems at: Project44, spanning ETA, risk, anomaly detection, and supply chain intelligence. This role sits at the intersection of applied modeling, platform thinking, and production impact, with a mandate to both ship high-value ML capabilities and build reusable Data Science platform primitives that scale across teams.
In addition, this role will drive the integration of Generative AI, LLMs, and: agentic systems into core workflows—enabling reasoning-driven diagnostics, automation, and intelligent decision support across the supply chain.
You will work closely with Data Science, ML Engineering, Data Engineering,: Platform, and Product teams to deliver production-grade systems and establish a scalable, repeatable approach to AI development at P44.
Drive High-Impact ML Systems Lead end-to-end development of models for ETA,: risk, anomaly, and fraud—leveraging advanced techniques (embeddings, transformers, hybrid models).
Build Data Science as a Platform Develop reusable ML infrastructure: (features, experimentation, deployment, monitoring) to scale model development and reduce time-to-production.
Lead GenAI & Agentic Systems Build LLM-powered solutions (RAG, diagnostics,: automation, coding agents) and establish guardrails, evaluation, and explainability.
What they're looking for
- Translate Business Problems into ML Solutions Convert customer workflows into: well-defined ML problems and ensure measurable business impact.
- Drive Experimentation & Evaluation Establish strong offline/online evaluation: frameworks tied to business outcomes.
- Collaborate Across Engineering Partner with MLE and DE to build scalable,: reliable systems across the ML lifecycle.
- Experience 8–10+ years in Data Science / Applied ML with a strong track: record of building and deploying production-grade ML systems.
