AI Application Development Engineer, Arista

• Arista Networks seeks a Software Developer with expertise in building and implementing advanced software tools, machine learning models, and NLP/LLM solution
• We value a proactive team player with attention to detail, strong problem-solving abilities, and experience with Agile frameworks
• If you're experienced in deploying large language models, NLP applications, and advanced ML methodologies, we’d love to connect
• Bachelor’s degree in Computer Science, Data Science, or a related field; or equivalent experience
• 5-8 years of experience in ML/NLP model development, with exposure to LLM applications
• Experience in deploying models in production environments, monitoring them and improving the performance
• Proficiency in Python and SQL
• Deep understanding of NLP techniques (tokenization, embeddings, transformers) and experience working with LLM frameworks such as Hugging Face Transformers, OpenAI API, or similar
• Solid foundation in data structures, data modeling, and software architecture
• Knowledge of statistical methods, probability, and algorithms, with a focus on text analytics
• Experience with ML frameworks like TensorFlow, PyTorch, Scikit-learn, and familiarity with NLP tools like spaCy or NLTK
• Proficiency in data visualization (Tableau, Power BI, Matplotlib)
• Familiarity with Jupyter Notebooks for collaborative research
• Experience in Agile development methodology
• Strong analytical, creative, and team-oriented mindset
• Willingness to learn and adopt new technologies
• Excellent communication skills and a troubleshooting mindset

Desirable

• The Application Development Engineer (ADE) will play a key role in developing ML-driven applications and leveraging LLMs to address complex, data-rich challenges, collaborating closely with cross-functional teams throughout the development lifecycle
• Work a team of Data Scientists in design, train and deploy models and partner with business users to train and fine tune before final deployment
• Collect, process, and clean large datasets from various structured and unstructured sources
• Develop NLP and LLM-based applications tailored to business needs, such as text analysis, summarization, and conversational agents
• Design, implement, and optimize machine learning and LLM models, including transformers and language generation techniques
• Apply statistical analysis, machine learning, and NLP techniques to solve complex, data-driven business problems
• Select appropriate data representation techniques for LLM models, including embeddings and tokenization
• Perform hyperparameter tuning, model evaluation, and retraining for LLMs and other ML systems as needed
• Develop and maintain data ingestion / parsing processes that support rapid prototyping and deployment of LLM-based solutions
• Visualize and present insights to stakeholders, leveraging data visualization tools
• Troubleshoot, debug, and enhance existing ML and AI systems
• Recommend and implement model improvements based on performance metrics
• Document technical processes, model architectures, and findings for reference and reporting
• Collaborate with cross-functional teams to develop and deploy data-driven, NLP-powered solutions
• Stay current with advancements in LLMs, and machine learning techniques