Senior Staff Machine Learning Engineer (AI Agent)
New
C
CrestaConversational AI
CanadaFull-TimeStaff
SalaryCompensation for this position includes a base salary, equity, and a variety of benefits.
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Job Details
- Experience
- 5–8+ years of industry experience building and deploying machine learning systems in production, including significant experience working with LLMs.
- Required Skills
- Machine LearningPyTorchTensorflowGenerative AI
Requirements
- Hold a Bachelor’s degree in Computer Science, Mathematics, or a related field; a Master’s or Ph.D. is preferred.
- Have 5–8+ years of industry experience building and deploying machine learning systems in production, including significant LLM experience.
- Bring strong expertise in NLP, Generative AI, transformer architectures, embeddings, and retrieval systems.
- Have experience designing and deploying Retrieval-Augmented Generation (RAG) systems in enterprise environments.
- Have experience building and evaluating complex agentic or multi-step LLM workflows.
- Know modern machine learning frameworks and tools such as PyTorch, TensorFlow, and Hugging Face.
- Have experience with distributed or cloud-based infrastructure.
- Demonstrate the ability to optimize real-time machine learning systems for performance, scalability, and reliability.
- Bring technical leadership skills and the ability to influence cross-functional decisions.
Responsibilities
- Lead the design and development of next-generation AI Agents and Agentic Assist systems, defining system architecture and core modeling approaches.
- Architect intelligent, multi-step agent workflows that combine real-time guidance, knowledge retrieval, reasoning, summarization, and automated actions.
- Design, deploy, and optimize LLM-powered systems, including Retrieval-Augmented Generation (RAG) pipelines, multi-agent orchestration, and domain-adapted models.
- Improve reasoning, planning, and tool-use capabilities in real-world AI applications.
- Develop evaluation strategies, including offline benchmarking, online experimentation, and LLM-as-a-judge methodologies.
- Diagnose and mitigate failure modes such as hallucinations, retrieval errors, tool misuse, prompt brittleness, and multi-step reasoning breakdowns.
- Define and measure quality metrics, including accuracy, faithfulness, task completion, latency, cost, and robustness.
- Optimize AI systems for scalability, latency, security, and cost efficiency in production environments.
- Collaborate with product, frontend, and backend teams to integrate AI capabilities into the platform.
- Mentor engineers, contribute to technical strategy, and help shape the roadmap for AI systems.
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