Requirements
- 3+ years of production ML/AI engineering experience
- Deep expertise in Python and ML ecosystem (PyTorch, HuggingFace)
- Hands-on experience with LangChain, LlamaIndex, or similar orchestration frameworks
- Experience with vector databases (Pinecone, Weaviate, pgvector)
- Proficiency with OpenAI, Anthropic, or Google APIs
- Strong software engineering practices (testing, documentation, code review)
- Experience deploying ML systems to production
Nice to Have
- Fine-tuning experience with open-source LLMs (Llama, Mistral)
- MLOps experience (MLflow, Weights & Biases, Kubeflow)
- Contributions to AI/ML open-source projects
- Research publications or conference presentations
About the Role
Our AI Practice is building the next generation of enterprise AI applications — not demos, but production systems handling millions of real transactions. As an AI/ML Engineer, you’ll be at the frontier, designing architectures and building systems that deliver measurable business value.
What You’ll Do
- Design and implement RAG systems, AI agents, and LLM pipelines
- Select and evaluate foundation models for specific use cases
- Build evaluation frameworks to measure AI system performance
- Optimize for cost, latency, and accuracy in production deployments
- Stay current with the rapidly evolving AI landscape and bring new capabilities to clients
- Write technical content for our blog and contribute to the AI community
Our AI Stack
LangChain / LangGraph, LlamaIndex, OpenAI GPT-4o, Anthropic Claude, Google Gemini, Pinecone, Weaviate, pgvector, FastAPI, Celery, Redis, PostgreSQL, Kubernetes.
Benefits & Perks
- Competitive salary + performance bonus
- 100% remote work with flexible hours
- 30 days PTO + local public holidays
- $5,000 annual learning & conference budget
- Access to cutting-edge AI compute resources
- Health insurance or equivalent stipend
- Equity participation plan