Machine Learning Engineer

What You’ll Do Build LLM apps (RAG, prompts, agents, guardrails, evaluation) Own ML lifecycle: data → training (LoRA/QLoRA) → deployment → monitoring Deploy scalable solutions on AWS (EKS/ECS/Lambda, SageMaker, Bedrock) Optimize training/inference (FSDP, DeepSpeed, vector DBs, GPUs) Set up MLOps: CI/CD, model tracking, governance, responsible AI Collaborate with product/UX to deliver impactful ML solutions Mentor team and lead technical decisions Perform EDA and domain-focused data research What You’ll Bring Required: 5–7 yrs experience (3+ yrs in production ML systems) 1+ yr hands-on with LLMs (RAG, fine-tuning, prompt engineering) Strong AWS experience (SageMaker, Bedrock, Lambda, etc.) Python, PyTorch, Hugging Face, vector DBs MLOps (CI/CD, Docker, Kubernetes, monitoring) Data engineering (ETL, Spark/Flink) Nice to Have: Distributed training, RLHF, Inferentia/Trainium Domain experience (asset/sustainability) ML security & compliance How You Work Outcome-driven and fast-iterating Strong engineering and production mindset Collaborative leader and mentor