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Job Description
A Machine Learning Engineer responsible for developing and deploying AI and ML solutions to enhance internal tools, automate processes, and drive innovation across the company's energy platform, working closely with cross-functional teams to solve complex, open-ended problems using state-of-the-art techniques.
Key Responsibilities
- Develop and prototype AI tools and systems using state-of-the-art techniques, including LLMs, RAG, finetuning, and reinforcement learning.
- Work across the entire product lifecycle to identify and validate new technology applications that bring value to the business.
- Collaborate with engineering teams to build, deploy, and maintain AI systems using Python and Kubernetes.
- Solve complex, ambiguous problems by rapidly exploring approaches and validating solutions.
- Stay current with advancements in AI and ML to inform problem-solving and innovation.
Requirements
- Proficiency in working with Large Language Models (LLMs), including customization with advanced Retrieval-Augmented Generation (RAG) techniques, finetuning, and reinforcement learning.
- Experience working closely with other engineers to build fast, scalable systems.
- Proficiency in using Python for developing AI solutions.
- Experience deploying systems in production environments using Kubernetes.
- Ability to work across the entire product lifecycle, including exploring new technologies, validating ideas with teams, and rapidly prototyping solutions.
- Comfort with ambiguity and the ability to identify approaches and validate them quickly.
- Strong knowledge of state-of-the-art techniques in machine learning and AI to solve complex problems.
- Experience working on internal AI tooling to improve developer productivity.
- Experience automating processes to reduce migration times for new clients.
- Educational background in a relevant field such as Computer Science, Data Science, or related disciplines (implied, as the role requires advanced technical skills).
Benefits & Perks
Competitive salary range (not specified)
Work environment with modern tools and infrastructure
Autonomy in work
Opportunities for professional development and staying up to date with field changes
Use of advanced AI techniques and technologies
Deployment of systems in production using Python and Kubernetes
Recognition as a Great Place to Work in multiple countries
High employee satisfaction score (e.g., 4.7 on Glassdoor in the UK)
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