It's fun to work in a company where people truly BELIEVE in what they are doing!
We're committed to bringing passion and customer focus to the business.
As the Lead for LLMOps, you will spearhead the development, deployment, and operationalization of large language model-based solutions. You’ll guide a team of AI/ML engineers and data scientists, manage the lifecycle of LLM applications, and ensure scalable, secure, and responsible AI implementations across the organization.
🔧 Key Responsibilities
Strategic Leadership
Define and drive the vision for LLMOps within the organization.
Collaborate with product and tribe leads to align LLM capabilities with business goals.
Lead pre-sales and proposal efforts for LLM-based solutions.
Technical Delivery
Architect and implement end-to-end LLM workflows including fine-tuning, evaluation, deployment, and monitoring.
Establish best practices for model governance, CI/CD pipelines, and responsible AI.
Oversee integration of LLMs with enterprise systems and APIs.
Team Management
Build and mentor a high-performing team of ML engineers and AI specialists.
Allocate resources effectively across global delivery backlogs.
Foster a culture of innovation, accountability, and continuous learning.
Partnerships & Ecosystem
Develop strategic partnerships with platforms like Hugging Face, LangChain, and cloud providers (AWS, Azure, GCP).
Stay abreast of emerging tools and frameworks in generative AI and LLMOps.
📚 Qualifications
Master’s or PhD in Computer Science, Machine Learning, NLP, or related field.
8+ years of experience in AI/ML, with at least 2 years in LLMOps or generative AI.
Proven track record of deploying LLMs in production environments.
Deep understanding of NLP architectures (Transformers, RNNs, CNNs).
Experience with LangChain, RAG pipelines, vector databases, and containerized workflows.
Strong grasp of cloud-native tools and MLOps frameworks.
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!
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