9 дней назад
Lead Software Engineer (NLP, Gen AI)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Lead Software Engineer (NLP, Gen AI) (AI/NLP): Building and deploying Python-based algorithms, data science packages, APIs, and Generative AI solutions for data-driven products with an accent on large language models, natural language processing, and unstructured text analysis. Focus on designing scalable architectures, improving models through experimentation, and building agentic AI systems with LangChain, LangGraph, Langfuse, RAG, and prompt engineering.
Location: Gurgaon, India; hybrid work environment
Company
provides research, consulting, and technology insights to enterprise leaders worldwide.
What you will do
- Design, implement, and deploy algorithms and Python-based applications for data-driven products and services.
- Establish methodologies for rapidly delivering AI, ML, and LLM-powered data analysis capabilities.
- Lead architecture and technical design discussions for data science solutions.
- Analyze unstructured text using machine learning, deep learning, and natural language processing techniques.
- Create reusable data science packages and APIs, ensuring scalability, stability, and business adoption.
- Mentor junior team members and promote effective technical practices and emerging AI technologies.
Requirements
- 7–9 years of experience with algorithms, statistics, data mining, machine learning, deep learning, and natural language processing.
- Experience with NLP, BERT, Transformers, deep learning, and machine learning models and techniques.
- Experience using LLMs such as OpenAI, Cohere, Anthropic, or Llama to deliver business outcomes.
- Experience building Generative AI and Agentic AI solutions with LangChain, LangGraph, Langfuse, RAG, and prompt engineering.
- Graduate or postgraduate degree in Engineering or Data Science; BE/BTech, ME/MTech, or MCA preferred.
- Ability to translate quantitative analysis into business strategies and collaborate with business, data science, and technical stakeholders in an Agile-Scrum environment.
Culture & Benefits
- Hybrid work environment with virtual work supported when productive and in-person collaboration in a community setting.
- Competitive compensation and benefits.
- Inclusive workplace with colleagues from diverse geographies, cultures, and backgrounds.
- Opportunities to work on AI initiatives and develop software, frameworks, and technology expertise.
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