About the job :

What Youll 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 Youll Bring :

Required :

- 5 - 12 yrs experience (3 yrs in production ML systems)
- 3 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
- Team-oriented leader and mentor

📌 Machine Learning Engineer (India)
🏢 Spectral Consultants
📍 India