Founding Machine Learning Engineer
Hybrid Working
Exciting Start-up AI Company
The Opportunity:
You will be joining the founding team with equity ownership in a fast-growing AI start-up and will be instrumental in defining the future of AI orchestration. You will lead the creation and integration of advanced systems that seamlessly manage interactions between AI models, cutting-edge tools, and human operators.
Required Qualifications:
Educational Background:
Advanced degree (Master's/PhD) in Computer Science, Machine Learning, Data Science, or a related field. Specialized Expertise:
Expertise in LLM frameworks, agent building, and prompt engineering. Professional Experience:
Over 5 years of experience in machine learning or applied research. Technical Knowledge:
Strong understanding of data structures, algorithms, and software engineering principles. Proven Capability:
Demonstrated success in deploying production-ready ML systems. Programming Skills:
Proficiency in Python and modern ML frameworks. Systems Experience:
Hands-on experience with distributed systems and microservices architecture. Desirable Skills: Cloud:
AWS/GCP/Azure Deep Learning Frameworks:
Experience with PyTorch and TensorFlow. Graph Databases:
Knowledge of graph databases and knowledge graphs.
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Advanced degree (Master's/PhD) in Computer Science, Machine Learning, Data Science, or a related field. Specialized Expertise:
Expertise in LLM frameworks, agent building, and prompt engineering. Professional Experience:
Over 5 years of experience in machine learning or applied research. Technical Knowledge:
Strong understanding of data structures, algorithms, and software engineering principles. Proven Capability:
Demonstrated success in deploying production-ready ML systems. Programming Skills:
Proficiency in Python and modern ML frameworks. Systems Experience:
Hands-on experience with distributed systems and microservices architecture. Desirable Skills: Cloud:
AWS/GCP/Azure Deep Learning Frameworks:
Experience with PyTorch and TensorFlow. Graph Databases:
Knowledge of graph databases and knowledge graphs.
#J-18808-Ljbffr
