AI Engineer
Role details
Job location
Tech stack
Job description
We are seeking an experienced technical leader to architect and scale our AI systems. You will bridge traditional machine learning with state-of-the-art Large Language Models (LLMs), acting as the technical anchor to drive our AI strategy from research to production., * System Architecture: Design, build, and scale secure, cost-effective ML pipelines and Generative AI applications.
- LLM Integration: Lead development using advanced RAG architectures, prompt engineering, and fine-tuning (PEFT/LoRA) on models like Llama 3, Gemini, and OpenAI.
- Core Machine Learning: Train and optimize predictive models, classifiers, and recommendation systems using deep learning and classical ML.
- MLOps & Leadership: Oversee model deployment (CI/CD for ML), monitor for drift, ensure AI safety, and mentor junior engineers.
Requirements
- 8-10 years in Machine Learning or Software Engineering, with 4+ years deploying Deep Learning models to production.
- 8+ years experience in Programming & Frameworks: Expert in Python; extensive hands-on experience with PyTorch (preferred) or TensorFlow.
- 4+ years experience in LLM Ecosystem: Deep knowledge of orchestration (LangChain, LlamaIndex), vector databases (Pinecone, Weaviate), and inference optimization (vLLM, quantization).
- 6+ years experience in Traditional ML & Data: Strong grasp of statistical modeling (scikit-learn, XGBoost) and large-scale data processing (Apache Spark, Ray).
- 6+ years experience in MLOps & Cloud: Proficiency with Cloud platforms (AWS/GCP/Azure), containerization (Docker, Kubernetes), model tracking (MLflow), and API deployment (FastAPI).
Education: Master's or Ph.D. in CS, AI, Math, or equivalent practical experience
Preferred: Open-source AI contributions, experience with multi-modal models, or a background in AI guardrails. "