Forward Deployed Engineer — AI/ML (5+ yrs MUST || After College)

**MarkAI** is an AI-native services company. We place forward-deployed engineers inside client teams to build and ship production AI systems. We're already live, with engineers deployed at well-known organisations. The team is hand-picked from top-tier college networks. We're not a body shop. You'll work next to the client's engineers, own outcomes end to end, and take a system from first prototype to production. ### What you'll do - Embed with client teams and turn business problems into working AI systems - Build agentic workflows and multi-step LLM pipelines with **LangGraph** - Design RAG systems: chunking, embeddings, vector search, reranking and evals - Build and tune classical ML models (**XGBoost, LightGBM**) for scoring, risk, ranking and forecasting, and combine them with LLMs where it makes sense - Fine-tune models (LoRA/PEFT, RL where needed) on proprietary data - Improve inference latency and cost (vLLM, batching, quantisation) - Ship production-grade services with monitoring, evals and guardrails - Own reliability once it's live. If it breaks, you're on it. ### Must have - **5+ years** of software/ML engineering, with at least 2 years shipping ML or LLM systems to production - Strong **Python** and backend fundamentals (FastAPI, async, testing) - **XGBoost / LightGBM**: feature engineering, tuning, evaluation - **LangGraph** (or LangChain / LlamaIndex) for agents and tool-calling - **Vector DBs**: pgvector, Pinecone, Qdrant, Weaviate or Milvus - **Embeddings**: model selection, hybrid search (BM25 + dense), rerankers - **LLM evals & observability**: Ragas, LangSmith, Langfuse - **Cloud & deployment**: AWS/GCP, Docker, Kubernetes, CI/CD - Comfortable talking directly to client stakeholders, from engineers to leadership ### Good to have - Fine-tuning (LoRA/QLoRA, DPO/RL), Hugging Face ecosystem - Inference serving: vLLM, TGI, Triton - Data pipelines: Spark, Airflow, Kafka - Fintech, payments or high-scale consumer background - Open-source contributions ### Why MarkAI - **₹25L – ₹50L**, based on depth and what you've shipped - Real production problems at scale, not demos - Small team, high ownership, direct access to the founder - Exposure across multiple companies and domains