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AI Engineer
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- Posted a day ago
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Job Description
Job Description
Key Responsibilities
Key Responsibilities
- Agentic AI Development : Work on building scalable multi-modal Large Language Model (LLM) based AI agents, leveraging frameworks such as LangGraph, Microsoft Autogen, or Crewai.
- AI Research and Innovation : Research and build innovative solutions to relevant AI problems, including Retrieval-Augmented Generation (RAG), semantic search, knowledge representation, tool usage, fine-tuning, and reasoning in LLMs.
- Technical Expertise : Proficiency in a technology stack that includes Python, LlamaIndex / LangChain, PyTorch, HuggingFace, FastAPI, Postgres, SQLAlchemy, Alembic, OpenAI, Docker, Azure, Typescript, and React.
- LLM and NLP Experience : Hands-on experience working with LLMs, RAG architectures, Natural Language Processing (NLP), or applying Machine Learning to solve real-world problems.
- Dataset Development : Strong track record of building datasets for training and/or evaluating machine learning models.
- Customer Focus : Enjoy diving deep into the domain, understanding the problem, and focusing on delivering value to the customer.
- Adaptability : Thrive in a fast-paced environment and are excited about joining an early-stage venture.
- Model Deployment and Management : Automate model deployment, monitoring, and retraining processes.
- Collaboration and Optimization : Collaborate with data scientists to review, refactor, and optimize machine learning code.
- Version Control and Governance : Implement version control and governance for models and data.
- Bachelor's degree in computer science, Software Engineering, or a related field
- 2-5 years of experience in MLOps, DevOps, or related roles
- Have strong programming experience and familiarity with Python based deep learning frameworks like Pytorch, JAX, Tensorflow
- Have strong familiarity and knowledge of machine learning concepts
- Proficiency in cloud platforms (AWS, Azure, or GCP) and infrastructure-as-code tools like Terraform
- Experience with experiment tracking and model versioning tools
- You have experience with technology stack: Python, LlamaIndex / LangChain, PyTorch, HuggingFace, FastAPI, Postgres, SQLAlchemy, Alembic, OpenAI, Docker, Azure, Typescript, React.
- Knowledge of data pipeline orchestration tools like Apache Airflow or Prefect
- Familiarity with software testing and test automation practices
- Understanding of ethical considerations in machine learning deployments
- Strong problem-solving skills and ability to work in a fast-paced environment
More Info
Key Skills
LangChain
HuggingFace
Alembic
OpenAI
LlamaIndex
About Company
Skills:
Nlp, Pytorch, Flask, Python, AWS, Ml, React, Gcp, FastAPI, Azure, pgvector, Qdrant, Hugging Face, CoT, Pinecone, ML pipelines, RAG pipelines, retraining schedules, LangChain, Generative AI, Ai, canary releases, Anthropic, Graph-of-Thought, FAISS, drift detection, Milvus, OpenAI, Weaviate, LlamaIndex
Skills:
Sql, Git, Rest Apis, Python, LangChain, NoSQL databases, vector databases, Claude, Pinecone, Machine Learning concepts, Hugging Face models, FAISS, ChromaDB, OpenAI Gemini, LlamaIndex, AI frameworks
Skills:
FastAPI, Redis, Python, AWS, PostgreSQL with pgvector, LLM APIs
Skills:
Tensorflow, Pytorch, Docker, AWS, MLops, Gcp, FastAPI, Azure, cloud AI deployments, pgvector, LLM landscape, vector databases, voice speech models, Scikit-Learn, TTS, Python-based ML AI systems, ChromaDB, fine-tuning LLMs, ASR, large-scale datasets, LoRA, RAG, LLM agent frameworks, Weaviate, QLoRA
Skills:
Apis, Random Forest, Docker, XGBoost, Python, LangChain, embeddings, n8n, LLMs, Pinecone, Semantic Kernel, Chroma, FAISS, RAG, LlamaIndex, Prompt Engineering