About Us:
Neuron7.ai is a rapidly growing AI-first SaaS company focused on creating a category-defining service intelligence product. Backed by top venture capitalists in Silicon Valley and a distinguished group of angel advisors/investors, we are recognized as a startup to watch. Our swift traction in the market underscores our mission to empower enterprises to make accurate service decisions at scale. Our AI-driven platform delivers service predictions in seconds by analyzing structured and unstructured data alongside insights from leading experts. In complex service environments—such as high-tech devices, manufacturing, and medical devices—Neuron7.ai helps service leaders excel in critical metrics like first-call resolution, turnaround time, and service margins.
Why Join Us:
At Neuron7.ai, you’ll be part of a dynamic and innovative team that is redefining service intelligence. We value creativity, collaboration, and a commitment to pushing boundaries.
About the Team:
As a Staff Data Scientist at Neuron7.ai, you will lead the design, development, and deployment of NLP-driven solutions for processing and analyzing large volumes of unstructured data. You will bring a deep technical skill set and a passion for innovation to launch impactful AI products to live users. You will also serve as a mentor to junior team members and collaborate closely with cross-functional teams and customers.
What You’ll Do:
- Lead the development and deployment of NLP-based solutions to process and analyze unstructured data at scale.
- Design, train, and optimize machine learning models using libraries such as PyTorch, NLTK, and Scikit-learn.
- Architect and deploy AI/ML products on cloud platforms like Azure, GCP, or AWS.
- Collaborate with data engineering teams to ensure seamless integration of AI models into production systems.
- Perform advanced SQL analytics to extract actionable insights from structured datasets.
- Stay up-to-date with the latest advancements in NLP and machine learning techniques.
- Mentor junior data scientists and foster a culture of technical excellence within the team.
- Communicate complex technical concepts to non-technical stakeholders and customers.
- Partner with customers to understand their needs and translate them into technical solutions.
What We’re Looking For:
- Minimum 8 years of experience in data science, with a focus on NLP and unstructured data processing.
- Proven track record of launching NLP-driven products to live users.
- Expertise in Python and standard libraries such as PyTorch, NLTK, and Scikit-learn.
- Experience with Transformer-based models (e.g., BERT, GPT).
- Develop, train, and optimize ML and deep learning models (classification, regression, clustering, sequence modeling, embeddings).
- Implement and fine-tune transformer-based models such as BERT, GPT-style LLMs, and domain-specific architectures.
- Build and deploy RAG (Retrieval-Augmented Generation) pipelines, vector databases, embedding models, and prompt optimization workflows.
- Strong experience with one or more cloud platforms (Azure, GCP, AWS) for hosting and deploying AI/ML products.
- Design and implement NLP pipelines for text classification, information extraction, topic modeling, semantic search, summarization, and conversational AI applications.
- Fine-tune pretrained LLMs and Hugging Face models for domain-specific tasks.
- Develop custom tokenizers, embeddings, and text-processing architectures.
- Familiarity with data engineering pipelines and best practices.
- Proficiency in SQL for analytics and data manipulation.
- Build, evaluate, and deploy GenAI models for text generation, document processing, knowledge retrieval, and agent-based automation.
- Integrate LLMs into production systems using APIs, LangChain, LlamaIndex, or custom frameworks.
- Design safety, evaluation, and monitoring processes for GenAI deployments.
- Excellent problem-solving skills and ability to work with large-scale datasets.
- Strong interpersonal and communication skills, with the ability to mentor team members and interact with customers effectively.
- Work with large-scale datasets using Python, SQL, Spark, Databricks, or cloud data platforms.
- Build ETL/ELT pipelines, feature stores, and model-serving infrastructures.
- Deploy ML models into production environments using Docker, Kubernetes, and CI/CD pipelines.
- Implement monitoring, observability, and retraining workflows.
- Mentor junior data scientists and provide technical oversight for AI/ML projects.
- Collaborate with cross-functional teams to define model requirements and success metrics.
- Own the full ML lifecycle from research to deployment and ongoing maintenance.
Preferred Skills:
- Knowledge of MLOps practices for model deployment and monitoring.
- Familiarity with tools like Airflow, Spark, or similar data processing frameworks.
- Background in working with customer-facing applications and APIs.
Tools & Technologies Required:
- Programming: Python, SQL, PyTorch, TensorFlow
- NLP/LLM: Hugging Face, Transformers, BERT, GPT models, LangChain, LlamaIndex
- RAG: Vector stores (FAISS, Pinecone, Chroma), embeddings, retrievers
- Cloud: AWS / GCP / Azure
- MLOps: MLflow, Airflow, Kubeflow, Docker, Kubernetes
- Visualization: Power BI, Tableau, matplotlib, seaborn