AI Engineer (Python, Machine Learning, Generative AI/LLMs)

Modus-create
United States
Workplace: RemoteFull timeFunction: Data Science & Machine LearningSkills: ["Collaboration","Software engineering fundamentals","Maintainability","Scalability","Testing"]

Design, build, and deploy intelligent AI solutions across the full AI/ML lifecycle, from experimentation and model development through integration and production deployment. Work with engineering, product, and data teams to turn business challenges into scalable AI-powered features using machine learning, deep learning, and generative AI/LLMs. Apply NLP techniques and Retrieval-Augmented Generation (RAG) pipelines, and support reliable MLOps with monitoring, CI/CD, and production workflows.

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FursaFursa
Modus-create
Modus-create
1 week ago

AI Engineer (Python, Machine Learning, Generative AI/LLMs)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 16 hours agoStatus: Live

Job Summary

Design, build, and deploy intelligent AI solutions across the full AI/ML lifecycle, from experimentation and model development through integration and production deployment. Work with engineering, product, and data teams to turn business challenges into scalable AI-powered features using machine learning, deep learning, and generative AI/LLMs. Apply NLP techniques and Retrieval-Augmented Generation (RAG) pipelines, and support reliable MLOps with monitoring, CI/CD, and production workflows.
Location: United States
Workplace: Remote
Employment Type: Full time
Job Function: Data Science & Machine Learning

Key Responsibilities

  • •Design, build, and deploy intelligent AI solutions across the AI/ML lifecycle, from experimentation and model development to production deployment.
  • •Collaborate with engineering, product, and data teams to integrate AI-powered capabilities into scalable applications.
  • •Develop and implement machine learning models, including evaluation and optimization for production use.
  • •Build NLP and generative AI features, including LLM-based applications and semantic retrieval capabilities.
  • •Apply MLOps practices for deployment reliability, including versioning, monitoring, and CI/CD for production ML workflows.

Key Requirements

  • •Strong proficiency in Python and experience building production-ready AI/ML applications and services.
  • •Solid experience across the machine learning lifecycle, including model development, evaluation, optimization, and implementation.
  • •Hands-on experience building applications with generative AI and large language models (LLMs).
  • •Practical experience with PyTorch and/or TensorFlow, plus NLP experience (e.g., text processing, embeddings, semantic search, classification, or generation).
  • •Experience designing and implementing RAG pipelines with vector-based retrieval, plus integrating AI/ML APIs, foundation models, and third-party AI services.
Experience:SaaSDeveloper toolsAI/MLGenerative AI
Skills:CollaborationSoftware engineering fundamentalsMaintainabilityScalabilityTesting
Languages:English
Tech Stack:PythonMachine LearningDeep LearningGenerative AILLMsPyTorchTensorFlowNatural Language ProcessingNLPRetrieval-Augmented GenerationRAGEmbeddingsSemantic searchVector-based retrievalMLOpsCI/CDModel monitoringData engineeringData pipelinesData transformation

Company Brief

Modus-create
Digital transformation consultancy delivering product design, cloud-native engineering, DevOps, and organizational change services to help enterprises build and scale modern digital products and platforms.
Industry: Consulting
Company Size: Medium (51 to 250 employees)
Growth: Established Company
Funding: Bootstrapped
Headquarters: Raleigh, United States
Founded: 2007
WebsiteLinkedIn