AI Tech Specialist

Ford Motor Company

. Design NLP/LLM/GenAI applications and products using robust coding practices .

Posted 10/14/2026full-timeChennai • IndiaSeniorLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and deploying NLP, LLM, and GenAI applications, with a strong focus on model development, performance monitoring, and multimodal AI pipelines. Proficient in utilizing advanced coding practices and frameworks to create scalable AI products.

Highest-signal resume keywords

NLP Application DevelopmentLLM Model ExpertiseMultimodal AI Pipeline DevelopmentREST API DeploymentGenerative AI Dataset Management

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

NLPLLMGenAIMachine LearningDeep LearningModel TrainingModel DeploymentData ProcessingChatbot DevelopmentImage Generation

Tools & Technologies

DockerKubernetesHugging FaceTensorFlowPyTorchScikit-learnNumPyPandasSpaCyLangChain

Certifications & Qualifications

Bachelor’s DegreeMaster’s Degree

Industry Keywords

Automotive IndustryConversational AgentsSequence ClassificationSemantic SearchText Data Processing

Tech Stack

Tools & technologies

DockerKubernetesNumpyPandasPyTorchScikit-LearnTensorflow

About the role

Key responsibilities & impact

Design NLP/LLM/GenAI applications and products using robust coding practices
Explore state-of-the-art models and techniques for automotive industry use cases
Conduct ML experiments to train and infer models
Build models that meet memory and latency constraints when needed
Deploy REST APIs or minimalistic NLP application UIs using Docker and Kubernetes
Showcase NLP/LLM/GenAI applications through web frameworks such as Dash, Plotly, and Streamlit
Converge multiple bots into multimodal LLM-powered super apps
Develop agentic workflows using AutoGen, Agentbuilder, and LangGraph
Build modular AI/ML products consumable at scale
Work alongside leading technical experts worldwide on products involving sequence/token classification, QA/chatbots, translation, semantic search, and summarization

Requirements

What you’ll need

8+ years of experience
Bachelor’s or Master’s Degree in Computer Science, Engineering, Maths or Science
Experience in LLM models like PaLM, GPT4, and Mistral
Experience across the complete GenAI model development lifecycle, including training, testing, deployment, and performance monitoring
Experience developing and maintaining multimodal AI pipelines involving text, image, and audio
Experience implementing real-world chatbots or conversational agents at scale with different data sources
Experience developing image generation/translation tools using latent diffusion models such as Stable Diffusion or Instruct Pix2Pix
Expertise handling large-scale structured and unstructured data
Experience handling large-scale generative AI datasets and outputs
Familiarity with deep learning theory and practices in NLP applications
Coding familiarity with ADK, A2A, AgentSkills, Ontology, Hugging Face, LangGraph, LangChain, Chainlit, TensorFlow and/or PyTorch, Scikit-learn, NumPy, and Pandas
Familiarity with two or more open-source NLP modules such as spaCy, TorchText, fastai.text, or FARM Haystack
Knowledge of fundamental text data processing, including regex, token/word analysis, spelling correction/noise reduction, sentence segmentation, and clustering-based insight derivation
Experience implementing real-world BERT or other transformer fine-tuned models for sequence classification, NER, or QA, from data preparation through deployment
Modern NLP/LLM courses or open competitions welcomed