Responsibilities
- Design, build, and deploy production-grade AI/ML solutions on cloud platforms (Azure, AWS, or GCP).
- Develop LLM-based applications, including RAG (retrieval-augmented generation), agent workflows, and tool-based reasoning systems.
- Build scalable AI services, APIs, and pipelines that integrate into enterprise platforms and business workflows.
- Partner with engineering, data, and product stakeholders to translate business needs into practical technical solutions.
- Implement strong engineering standards for deployment, monitoring, reliability, and iteration.
- Contribute to MLOps practices using tools such as Docker, Kubernetes, MLflow, CI/CD, and observability tooling.
- Support model evaluation and continuous improvement to ensure quality, performance, and measurable impact.
Basic qualifications
- 5+ years of software engineering experience with strong coding skills (Python required; C#, Java, or similar languages a plus).
- 2+ years of hands-on experience using ML frameworks such as PyTorch, TensorFlow, Hugging Face, or similar.
- Proven experience applying LLMs, Generative AI, or agent-based frameworks to real business solutions.
- Demonstrated success delivering at least one ML/AI application or service into production at meaningful scale.
- Strong understanding of ML fundamentals, deep learning concepts, and applied optimization techniques.
- Familiarity with scalable deployment practices and MLOps tools (Docker, Kubernetes, MLflow, etc.).
- Strong analytical and communication skills with the ability to influence stakeholders and drive alignment.
Preferred qualifications
- Experience with RAG pipelines, embeddings, semantic search, and vector databases (FAISS, Pinecone, Weaviate, pgvector, etc.).
- Familiarity with LangChain, LlamaIndex, or open-source orchestration frameworks.
- Experience with evaluation frameworks, monitoring, and responsible AI practices.
- Experience optimizing inference for performance, latency, and cost.
- Advanced degree in AI/ML, Computer Science, Data Science, or related field (great plus but not required).
Benefits
- Medical, dental, and vision coverage
- 401(k) with employer match
- Generous paid time off and paid holidays
- Parental leave
- Hybrid/remote flexibility
- Professional development support
- Great discounts on worldwide stays
Tags & focus areas
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