Responsibilities
- Research & Innovation - Stay current with the latest LLM research, architectures, and advancements in the field including real-time models and multimodal systems.
- Research & Innovation - Evaluate emerging techniques and methodologies for potential application to business problems.
- Research & Innovation - Monitor developments in transformer architectures, fine-tuning approaches, model optimization, and real-time inference.
- Research & Innovation - Research and assess new LLM capabilities, frameworks, and API features as they emerge.
- Solution Design & Prototyping - Identify and define approaches for complex AI challenges leveraging state-of-the-art LLMs.
- Solution Design & Prototyping - Design and build proof-of-concept solutions to validate technical feasibility.
- Solution Design & Prototyping - Rapidly prototype LLM-based applications using modern frameworks and orchestration tools.
- Solution Design & Prototyping - Conduct rigorous experiments to evaluate different approaches and methodologies.
- Solution Design & Prototyping - Work collaboratively in multi-disciplinary team environments and establish professional networks with subject matter experts.
- Production Development & Software Engineering - Write clean, maintainable, production-quality code following software engineering best practices and design patterns.
- Production Development & Software Engineering - Develop robust, scalable agentic workflows using orchestration frameworks (such as LangGraph, CrewAI, or similar).
- Production Development & Software Engineering - Implement advanced LLM features, including tool calling, function calling, structured outputs, and multi-turn conversations.
- Production Development & Software Engineering - Build production-grade systems utilizing Model Context Protocol (MCP) and other emerging standards.
- Production Development & Software Engineering - Design and implement scalable, fault-tolerant architectures for real-time LLM-powered applications.
- Production Development & Software Engineering - Conduct thorough code reviews and maintain high code quality standards.
- Production Development & Software Engineering - Optimize code for performance, memory efficiency, and cost-effectiveness in production environments.
- Experimentation & Optimization - Design rigorous experiments to test hypotheses and validate model performance.
- Experimentation & Optimization - Develop evaluation frameworks for LLM outputs, system performance, and user experience.
- Experimentation & Optimization - Optimize prompt engineering strategies, fine-tuning approaches, and inference efficiency.
- Experimentation & Optimization - Conduct A/B tests, performance benchmarking, and statistical analysis.
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
Nice to Have
- Experience with voice/speech models and real-time audio processing (OpenAI Realtime API or similar)
- Knowledge of Model Context Protocol (MCP) and emerging LLM standards
- Experience with MLOps tools and practices (model monitoring, versioning, A/B testing)
- Contributions to open-source ML/AI projects or published research papers
- Familiarity with streaming architectures and event-driven systems (Kafka, RabbitMQ)
Additional Information
- Netomi is an equal opportunity employer committed to diversity in the workplace.
- We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, disability, veteran status, and other protected characteristics.
- We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses.
- These tools assist our recruitment team but do not replace human judgment.
- Final hiring decisions are ultimately made by humans.
- If you would like more information about how your data is processed, please contact us.