Sr. AI/ML Engineer
Indexed description
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.
Required Qualifications:
- Bachelor's degree in computer science, Software Engineering, or a related field
- 5-8 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
Desired Skills:
- Experience with experiment tracking and model versioning tools.
- You have experience with technology stack: Python, LlamaIndex / LangChain, PyTorch, HuggingFace, FastAPI, Postgres, SQL Alchemy, 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
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