Senior AI / ML Engineer
Role Overview
We are looking for an AI Engineer to build core AI capabilities and intelligent applications. This role spans data engineering, LLM training and fine-tuning, API development, and agentic application design. You will collaborate with product, data, and engineering teams to deliver scalable, reproducible pipelines and advanced AI-driven solutions.
Key Responsibilities
We believe in ownership, creativity, and continuous learning.
- Design and maintain reproducible data ingestion and transformation pipelines; ensure data quality, governance, and compliance for structured and unstructured datasets.
- Strong systems-thinking ability to design modular, scalable, and reproducible AI pipelines across data ingestion, corpus engineering, training, and deployment.
- Support domain-adaptive pre-training (DAPT) and fine-tuning (SFT, LoRA/QLoRA/PEFT) for specialized tasks; implement cost/performance optimizations (quantization, checkpointing, hyperparameter tuning).
- Strong understanding of tokenization, sequence packing, context length trade-oAs, and their impact on memory and training eAiciency.
- Develop AI agents capable of reasoning, planning, and executing multi-step workflows; integrate tools, APIs, and external data sources for autonomous task execution.
- API Development & Integration: Build and expose model services via RESTful APIs or gRPC for seamless integration; collaborate on architecture decisions for scalable serving stacks (vLLM/TGI/FastAPI).
- Implement end-to-end RAG pipelines: chunking, embeddings, vector indexing, retrieval, and grounded generation.
- Evaluation & Safeguards: Measure retrieval and generation quality using metrics (recall@k, MRR, nDCG, faithfulness); implement safeguards: citation enforcement, refusal policies, and uncertainty signaling.
- Documentation & Collaboration: Maintain experiment logs, configs, and reproducibility checklists; work cross-functionally to integrate AI solutions into enterprise applications.
- Lead and guide team members, providing technical direction while actively contributing as a hands-on engineer
Required Skills & Experience
- 5-6 years of hands-on experience in AI/ML/NLP engineering with shipped projects.
- Strong Python skills; experience with PyTorch and modern ML frameworks.
- Proficiency in data engineering (ETL pipelines, SQL/NoSQL, data validation).
- Experience with API development (FastAPI, Flask, or similar).
- Familiarity with Linux, Git, Docker, and MLOps practices (tracking, reproducibility).
- Strong communication and collaboration skills.
Preferred / Good to Have
- Exposure to multi-GPU training stacks (DeepSpeed/FSDP) and mixed-precision training.
- Experience serving LLMs and optimizing inference (quantization, batching, caching).
- Knowledge of agentic frameworks (LangChain, AutoGen, or similar).
- Familiarity with vector databases (e.g., Pinecone, Weaviate) and RAG evaluation tools.
- Understanding of knowledge graphs and entity-centric evaluation.
- Cloud experience (Azure/AWS/GCP), Kubernetes, and secure deployments.
Education
Minimum: B.E./B.Tech/M.E./M.Tech/M.Sc. in Computer Science, AI/ML, Data Science, or related field (or equivalent practical experience).
How to Apply
Send your resume and portfolio to shakhawatmiya@gmail.com
We review every application carefully.
