Senior Engineer I - Knowledge Graph Ml Engineer - Gen Ai And Nlp

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Job Description:
We are looking for an experienced ML Engineer with significant expertise in Generative AI (GenAI), Natural Language Processing (NLP), and Machine Learning (ML) with preferable experience in building Automated Knowledge Graph pipelines. The ideal candidate will lead the design and implementation of knowledge graph systems. Contributionsto the development of AI-driven solutions, such as chatbots, advanced Document QA systems are also expected. The Ideal candidate would have hands-on experience in building and benchmarking Retrieval-Augmented Generation (RAG) techniques to enhance data retrieval for Gen-AI applications.
Key Responsibilities:
Lead the design, development, and deployment of knowledge graph architectures, including ontology and relationship mapping for enterprise-level projects.
Implement cutting-edge Generative AI techniques, including the development of fine-tuned language models and chatbot systems for intelligent query processing.
Collaborate with cross-functional teams to integrate NLP techniques such as text summarization, sentiment analysis, and topic modelling into enterprise applications.
Develop and maintain advanced ML models (both supervised and unsupervised), optimizing for performance and scalability.
Use LLMs (Large Language Models) for entity extraction, summarization, and text classification applications.
Work on RAG (Retrieval-Augmented Generation) systems, improving data retrieval and augmentation processes for enhanced performance in AI applications.
Design and optimize graph databases to store and query large knowledge graphs efficiently.
Utilize graph query languages (e.g., Cypher, Gremlin, or SPARQL) to extract relevant data from knowledge graphs and integrate it with other systems.
Build Native cloud environments based applications with a focus on deploying scalable ML solutions using tools like Vertex AI and Azure OpenAI services.
Drive the end-to-end project lifecycle, from requirements gathering to deployment and post-production support, ensuring that AI/ML solutions align with business goals.
Regularly engage with stakeholders, presenting AI-driven solutions that enhance business outcomes.

Core Competencies:
Expertise in Knowledge Graph Engineering, ontology creation, and entity-relation modelling.
Proficiency in Generative AI, NLP, and Machine Learning algorithms and frameworks.
Strong hands-on experience with LLM-based architectures such as OpenAI's GPT models, LlamaIndex, Llamaparse and LangChain.
Proven ability to implement advanced NLP solutions including named entity recognition (NER), Coreferencing, text classification, and topic modelling.
Proficiency with graph databases (e.g., Neo4j, cassandra) and graph query languages (e.g., Cypher, Gremlin, SPARQL).
Proficiency with Big Data tools (Hadoop, Spark) and cloud platforms like GCP, with deep knowledge of tools such as Vertex AI, Cloud Functions, and Dataflow.
Experience in developing and fine-tuning AI/ML models and scaling them for production.
Solid programming experience with Python, TensorFlow, Pytorch, and scikit-learn.

Qualifications:
Bacheleors / Master's degree in Computer Science, Information Technology, Artificial Intelligence, Machine Learning, or related fields.
Minimum 7+ years of experience in AI, ML, NLP, and Knowledge Graph Engineering.
Proven expertise in building and deploying knowledge graph systems and integrating them with NLP and ML solutions.
Proven ability to manage end-to-end Generative AI projects from concept to deployment.

Desired Skills:
Strong knowledge of NLP frameworks like SpaCy, NLTK, and Transformer-based models.
Familiarity with Microsoft Graph and RAG techniques to enhance AI-powered search and retrieval systems.
Experience with cloud-based AI/ML tools (GCP, Azure) and containerization technologies such as Docker and Kubernetes.
Familiarity with modern ML/AI workflows, including CI/CD pipelines, and experience with tools like MLFlow and Jenkins.

Soft Skills:
Excellent problem-solving abilities with a focus on innovation.
Strong communication and collaboration skills, with the ability to work with cross-functional teams.
Leadership capabilities, including managing complex projects and mentoring junior team members.

Why Join Us?:
Work on the cutting edge of AI and NLP innovation.
Opportunity to collaborate with industry leaders and work on impactful projects.

A dynamic, fast-paced environment that encourages learning and growth.
We back our colleagues and their loved ones with benefits and programs that support their holistic well-being. That means we prioritize their physical, financial, and mental health through each stage of life. Benefits include:
Competitive base salaries 
Bonus incentives 
Support for financial-well-being and retirement 
Comprehensive medical, dental, vision, life insurance, and disability benefits (depending on location) 
Flexible working model with hybrid, onsite or virtual arrangements depending on role and business need 
Generous paid parental leave policies (depending on your location) 
Free access to global on-site wellness centers staffed with nurses and doctors (depending on location) 
Free and confidential counseling support through our Healthy Minds program 
Career development and training opportunities

American Express is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other status protected by law.  
Offer of employment with American Express is conditioned upon the successful completion of a background verification check, subject to applicable laws and regulations.