We're partnering with a global leader in the energy and commodities space that's making a long-term investment in applied AI. They're hiring a Senior Machine Learning Engineer to lead hands-on efforts in building and deploying large-scale models that directly impact real-world decisions. This is a rare opportunity to help define how machine learning integrates across a multi-billion-dollar trading operation - all within a collaborative, flat, and engineering-driven environment.
What You'll Do
- Architect and deploy machine learning systems from first principles - including GenAI and LLM-based applications
- Partner closely with technical leads and business stakeholders to shape use cases and prioritize model development
- Own projects end-to-end: from data ingestion and feature engineering to experimentation and production rollout
- Translate complex requirements into scalable, modular code in Python
- Integrate models into internal tools and platforms, enhancing decision-making for commercial and trading teams
- Collaborate with global teams (Europe & U.S.) on model design, tooling standards, and cross-region initiatives
What We're Looking For
- 5-7+ years of experience developing and deploying ML models in production environments
- Deep fluency in Python and ML frameworks (eg, PyTorch, TensorFlow, Transformers)
- Demonstrated experience applying LLMs or GenAI to real-world business problems
- Familiarity with modern cloud infrastructure (eg, AWS) and containerization (eg, Docker)
- Strong communication skills and ability to work across technical and non-technical teams
- A product mindset with the ability to build, iterate, and refine based on feedback
- Preference for candidates with experience in high-scale or data-rich domains like finance, trading, or logistics
- Master's or PhD in Computer Science, Machine Learning, Data Science, or related field preferred