Posted:4 days ago|
Platform:
Work from Office
Full Time
We are seeking a highly experienced and technically adept Lead AI/ML Engineer to spearhead the development and deployment of cutting-edge AI solutions, with a focus on Generative AI and Natural Language Processing (NLP). The ideal candidate will be responsible for leading a high-performing team, architecting scalable ML systems, and driving innovation across AI/ML projects using modern toolchains and cloud-native technologies. Key Responsibilities Team Leadership: Lead, mentor, and manage a team of data scientists and ML engineers; drive technical excellence and foster a culture of innovation. AI/ML Solution Development: Design and deploy end-to-end machine learning and AI solutions, including Generative AI and NLP applications. Conversational AI: Build LLM-based chatbots and document intelligence tools using frameworks like LangChain , Azure OpenAI , and Hugging Face . MLOps Execution: Implement and manage the full ML lifecycle using tools such as MLFlow , DVC , and Kubeflow to ensure reproducibility, scalability, and efficient CI/CD of ML models. Cross-functional Collaboration: Partner with business and engineering stakeholders to translate requirements into impactful AI solutions. Visualization & Insights: Develop interactive dashboards and data visualizations using Streamlit , Tableau , or Power BI for presenting model results and insights. Project Management: Own delivery of projects with clear milestones, timelines, and communication of progress and risks to stakeholders. Required Skills & Qualifications Languages & Frameworks: Proficient in Python and frameworks like TensorFlow , PyTorch , Keras , FastAPI , Django NLP & Generative AI: Hands-on experience with BERT , LLaMA , Spacy , LangChain , Hugging Face , and other LLM-based technologies MLOps Tools: Experience with MLFlow , Kubeflow , DVC , ClearML for managing ML pipelines and experiment tracking Visualization: Strong in building visualizations and apps using Power BI , Tableau , Streamlit Cloud & DevOps: Expertise with Azure ML , Azure OpenAI , Docker , Jenkins , GitHub Actions Databases & Data Engineering: Proficient with SQL/NoSQL databases and handling large-scale datasets efficiently Preferred Qualifications Masters or PhD in Computer Science, AI/ML, Data Science, or related field Experience working in agile product development environments Strong communication and presentation skills with technical and non-technical stakeholders
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