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Knowledge Graph Engineer at Johnson & Johnson focusing on biomedical data standardization and interoperability solutions. Contributing to healthcare innovation through data - driven technologies and collaborations.
About the role
- Lead Data Scientist developing NLP-driven solutions for large volumes of unstructured data. Join AI-first SaaS company Neuron7.ai pushing the boundaries of service intelligence.
Responsibilities
- 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.
Requirements
- 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.
Benefits
- Competitive salary, equity, and spot bonuses.
- Paid sick leave.
- Latest MacBook Pro for your work.
- Comprehensive health insurance.
- Paid parental leave.
- Work from our vibrant Bengaluru office.
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
No Education Requirement
Tech skills
Location requirements
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