2 Corenlp Jobs

Overview: We are seeking an exceptional and technically accomplished Senior Data Scientist to join our rapidly growing team. This role is ideal for a hands-on AI expert with deep experience in Large Language Models (LLMs) , Natural Language Processing (NLP) , Cognitive AI , Conversational AI , and Agentic AI systems . You will work on designing, developing, and scaling state-of-the-art AI solutions that drive business innovation, operational intelligence, and customer experience transformation. This is a high-impact individual contributor role, focused on technical excellence and product-grade AI development. Key Responsibilities LLM & Cognitive AI Solution Development Architect and fine-tune LLM-based solutions (e.g., GPT, LLaMA, Claude, Mistral) using transfer learning, PEFT, and retrieval-augmented generation (RAG). Develop Agentic AI architectures with autonomous behavior and multi-agent collaboration capabilities. Apply prompt engineering , in-context learning , and tool former-style techniques to enable complex reasoning and task execution. Build Conversational AI systems using Transformer-based backbones and orchestration tools (LangChain, Haystack, Rasa, Semantic Kernel). Natural Language Processing (NLP) Design and implement advanced NLP pipelines for semantic search, summarization, NER, text classification, and knowledge extraction. Utilize and integrate tools such as SpaCy , BERT , RoBERTa , GloVe , Word2Vec , NLTK , and TextBlob . Conduct advanced text preprocessing, dependency parsing, sentiment analysis, tokenization, and multilingual NLP modeling. AI/ML Engineering Build scalable ML pipelines with FastAPI, gRPC, and RESTful interfaces. Containerize services using Docker and deploy to production environments via Kubernetes and cloud-native workflows. Integrate models into real-time and batch data systems, optimizing for latency, throughput, and reliability. Cloud & Infrastructure Develop and deploy solutions on AWS , Azure , or Google Cloud Platform (GCP) . Leverage services like SageMaker, Vertex AI, Azure ML Studio, and serverless orchestration tools. MLOps & CI/CD Design and maintain end-to-end MLOps pipelines using tools like MLflow, Kubeflow, or TFX for reproducibility and traceability. Automate model testing, monitoring, versioning, and rollback strategies in production. Big Data & Analytics Apply Spark, Hadoop, and Hive to process large-scale datasets efficiently. Perform complex data transformations and statistical modeling to extract actionable insights. Database & Data Engineering Interface with SQL and NoSQL systems (PostgreSQL, MongoDB, DynamoDB, etc.) for efficient data retrieval and processing. Design data schemas and optimize query performance for AI-centric applications. Cross-functional Collaboration Work closely with product managers, engineers, and domain experts to identify high-impact problems and deliver AI-driven solutions. Communicate findings and solution architectures clearly to technical and non-technical stakeholders. Technical Skills Expert in Python , PyTorch, HuggingFace Transformers, LangChain, and OpenAI/Anthropic/LLama APIs. Deep understanding of Transformer architectures , Attention Mechanisms , and LLM fine-tuning techniques . Familiarity with Agentic AI paradigms , including memory management, autonomous goal completion, and tool use. Strong experience with cloud platforms, container orchestration (Docker + Kubernetes), and deployment automation. Proficient in statistical modeling, probabilistic reasoning, and experimental design. Bonus Experience in Online Reputation Management (ORM) or product-centric platforms . Publications or open-source contributions in AI/ML/NLP.

Role Overview: We' re looking for a Lead Data Scientist to join our fast-growing, mission-driven team. This is a high-impact leadership role at the intersection of technology, strategy, and innovation where your expertise will power intelligent solutions that redefine how we think about data, products, and customer experience. If you thrive in high-performance environments and want to lead cutting-edge projects with Generative AI, LLMs, and large-scale NLP systems, this is your opportunity to make a lasting impact. Key Responsibilities: Build the Future with AI/ML Architect scalable AI systems to solve real-world, high-value business challenges cross domains. Design and deploy cutting-edge solutions with Generative AI, Transformer architectures, and custom Large Language Models (LLMs). Apply state-of-the-art ML techniques prompt engineering, transfer learning, multi-modal learning to push the boundaries of what's possible. NLP at Scale Lead the development of advanced NLP systems: semantic search, question answering, summarization, classification, and conversational AI. Work with best-in-class models and libraries: BERT, GPT, RoBERTa, Word2Vec, SpaCy, NLTK, Hugging Face Transformers, and more. Leverage language understanding to transform unstructured data into strategic insights. Full-Lifecycle Model Deployment Build robust MLOps pipelines for training, testing, deployment, and monitoring using MLflow, Kubeflow, Airflow, and CI/CD tools. Containerize and orchestrate AI models using Docker and Kubernetes across cloud environments (AWS, GCP, Azure). Design APIs and inference services using FastAPI or gRPC, optimized for performance, scalability, and uptime. Lead, Inspire, and Elevate Build and mentor a world-class data science team, nurturing talent and fostering a culture of curiosity, experimentation, and technical excellence. Drive the data science strategy, influence key decisions, and align AI initiatives with business goals. Establish best-in-class practices for model development, code quality, documentation, and performance evaluation. Data at the Core Work hands-on with structured, semi-structured, and unstructured data. Optimize high-volume data pipelines, integrate with SQL and NoSQL databases, and leverage big data ecosystems like Spark, Hive, and Hadoop. Use statistical modeling and experimental design to derive actionable intelligence from data Collaborate Across the Enterprise Work closely with engineering, product, and executive teams to define problems, explore solutions, and deliver AI products that move the needle. Translate technical concepts into strategic recommendations and insights that influence roadmaps and revenue. Champion AI literacy and advocate for ethical, explainable, and scalable data science across the organization. Education Bachelors or Master’s in Computer Science, AI, Data Science, Machine Learning, Engineering, or a related technical discipline. PhD is a plus. Experience 6+ years of experience in data science or machine learning, with 2+ years in a leadership or managerial role. Proven record of building and deploying AI solutions at scale in real-world production environments. Experience in GenAI, NLP, cloud-native architectures, and full-cycle ML development. Technical Expertise Languages & Libraries: Python, Scikit-learn, PyTorch, TensorFlow, Hugging Face, NumPy, Pandas NLP: BERT, GPT, Word2Vec, SpaCy, NLTK, TextBlob, CoreNLP, Transformer-based architectures Cloud & Deployment: AWS, Azure, GCP, Docker, Kubernetes, FastAPI, gRPC Big Data: Spark, Hive, Hadoop, Kafka Data Systems: PostgreSQL, MongoDB, Cassandra, Snowflake, BigQuery MLOps & Monitoring: MLflow, Airflow, Kubeflow, Prometheus, Grafana Nice to Have Experience in online reputation management, customer analytics, or product-led organizations. Familiarity with responsible AI, fairness, and explainability techniques (SHAP, LIME).