Key skills
AWSAzureCloudDockerGoogle Cloud PlatformPythonPyTorchTensorflowAIMachine LearningMLDeep LearningNLPLLMOpenAITensorFlowLangChainLangGraphPineconeWeaviatePytestGCPGoogle CloudGitVersion Control
About this role
Role Overview
- Stay current with the latest LLM research, architectures, and advancements in the field including real-time models and multimodal systems.
- Identify and define approaches for complex AI challenges leveraging state-of-the-art LLMs.
- Write clean, maintainable, production-quality code following software engineering best practices and design patterns.
- Design rigorous experiments to test hypotheses and validate model performance.
- Conduct thorough code reviews and maintain high code quality standards.
Requirements
- 3-5 years of experience in data science, machine learning, and AI development with strong focus on NLP and LLM applications
- Bachelor's/Master's or higher degree in Computer Science, Machine Learning, Statistics, or related technical field
- Proven track record of building and deploying production ML/AI systems from research to deployment
- Mastery of Python with strong software engineering fundamentals (OOP, design patterns, testing)
- Deep hands-on experience with LLM frameworks and APIs (OpenAI, Anthropic, or similar)
- Strong experience with at least one deep learning framework (PyTorch or TensorFlow)
- Proficiency with modern ML orchestration and agentic frameworks (LangGraph, CrewAI, LangChain, or similar)
- Solid understanding of NLP techniques: embeddings, information extraction, semantic search, classification
- Experience with diverse ML models: neural networks, transformers, SVM, Random Forest, clustering, Bayesian models
- Hands-on experience with advanced LLM features: tool calling, function calling, multi-turn conversations, structured outputs
- Strong knowledge of software development practices: version control (Git), testing (pytest)
- Experience with REST APIs, async programming, and building scalable backend services
- Familiarity with vector databases and embedding systems (Pinecone, Weaviate, FAISS, or similar)
- Knowledge of distributed computing, cloud platforms (AWS, GCP, or Azure), and containerization (Docker)
- Strong experimental design skills with ability to formulate hypotheses and conduct rigorous analysis
- Excellent problem-solving abilities and intellectual curiosity to stay current with AI research
- Self-motivated with proven ability to work collaboratively in multi-disciplinary teams
Tech Stack
- AWS
- Azure
- Cloud
- Docker
- Google Cloud Platform
- Python
- PyTorch
- Tensorflow
Benefits
- Netomi is an equal opportunity employer committed to diversity in the workplace.