ML Engineer

This role is with a Calyptus partner.

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As part of the Founding Team, you'll be at the forefront of defining how AI

orchestration works at scale. You will co-lead and propel our Machine Learning team to define how Human x AI orchestration works at scale. Working in tandem with our CTO, you will develop and integrate sophisticated orchestration systems that intelligently coordinate between a multitude of AI models, emerging tooling, and human workers. NLP and agent orchestration are key to this role.

Your Responsibilities

• Pioneer the development and implementation of AI agents for autonomous task execution within our orchestration platform
• Design and implement sophisticated systems for intelligent task planning, delegation, and coordination between AI agents and human workers
• Architect and build scalable, production-ready systems in cloud environments (AWS), with a focus on performance, reliability, and cost optimisation
• Develop and implement complex workflows for task routing and execution across multiple AI models and human operators
• Create robust monitoring and evaluation systems to track agent performance and workflow efficiency
• Integrate various AI models and tools into our orchestration layer, ensuring seamless interoperability
• Work with relational, non-relational, and graph databases to manage and process data efficiently
• Drive technical initiatives independently, from problem identification through solution implementation
• Contribute to the development of our core orchestration engine and its underlying architecture
• Self-manage complex projects while maintaining clear communication with stakeholders

Required Experience

Your experience will match well with the following. We are not box tickers. Above all,

we value drive, work rate, and tenacity.

Education and Qualifications

• Master's/PhD degree in Computer Science, Machine Learning, Data Science, or a related field

Technical Skills and Experience:

• 5+ years of professional machine learning experience or applied research in a
• related field
• Strong foundation in data structures, algorithms, and software engineering
• principles
• Demonstrated experience with LLM frameworks and agent building architectures
• Familiarity with prompt engineering and LLM optimisation techniques
• Proven track record of building and deploying production-ready ML systems
• Strong programming skills in Python and experience with modern ML frameworks
• Experience with distributed systems and microservices architecture
• Excellent problem-solving skills and ability to work in ambiguous, fast-paced environments
• Strong critical thinking skills with the ability to effectively evaluate and critique technical solutions
• Strong communication skills and ability to collaborate effectively with cross-functional teams

Strong Candidates May Also Have

• Experience with orchestration systems or workflow management platforms
• Strong knowledge of cloud architecture principles and best practices (particularly AWS)
• Proficiency in deep learning frameworks like PyTorch or TensorFlow
• Experience with end-to-end LLM training and fine-tuning
• Experience with real-time systems and event-driven architectures
• Knowledge of AI safety and alignment principles
• Background in reinforcement learning or multi-agent systems
• Experience with graph databases and knowledge graphs
• Contributions to open-source projects or research publications in relevant fields

You don’t need 100% of the above experience to be a good match!

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