4 дня назад
AI Engineer (Python, Machine Learning, Generative AI/LLMs)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
AI Engineer (Python, Machine Learning, Generative AI/LLMs) (AI/ML): Designing, building, and deploying intelligent solutions across the AI/ML lifecycle with an accent on production-ready Python services, generative AI, LLMs, NLP, and RAG pipelines. Focus on integrating foundation models, developing MLOps workflows, and building scalable AI applications with strong reliability, testing, and code quality.
Location: Fully remote
Company
is a digital product engineering partner that designs, builds, and scales custom solutions for forward-thinking businesses and Fortune 500 companies.
What you will do
- Design, build, and deploy intelligent solutions using machine learning, deep learning, and generative AI technologies.
- Work across the AI/ML lifecycle, from experimentation and model development through integration and production deployment.
- Build production-ready AI/ML applications and services in Python.
- Develop NLP, LLM, and retrieval-augmented generation solutions using vector-based retrieval.
- Integrate AI/ML APIs, foundation models, and third-party AI services into applications.
- Collaborate with engineering, product, and data teams to solve complex business challenges with scalable AI solutions.
Requirements
- Strong Python proficiency and experience developing production-ready AI/ML applications and services.
- Experience with machine learning model development, evaluation, optimization, and implementation.
- Hands-on experience with generative AI, large language models, deep learning, neural networks, and modern model architectures.
- Practical experience with PyTorch and/or TensorFlow, as well as natural language processing.
- Experience designing RAG pipelines, vector-based retrieval, AI/ML API integrations, MLOps, model deployment, data pipelines, and storage.
- Strong software engineering fundamentals, including maintainability, scalability, testing, code quality, and collaboration in a distributed environment.
Nice to have
- Experience with LLM fine-tuning, prompt engineering, model evaluation, vector databases, embeddings, and semantic retrieval.
- Exposure to AI agents, tool or function calling, and multi-agent architectures.
- Experience with cloud AI/ML platforms, containerization, orchestration, AI observability, guardrails, responsible AI, or model governance.
- Experience optimizing AI applications for performance, latency, scalability, and cost.
Culture & Benefits
- Fully remote collaboration in a distributed environment.
- Work on AI-powered products with real-world scale and impact.
- Collaborate closely with engineering, product, and data teams.
- Contribute to AI engineering standards, reliability, and responsible development practices.
- Explore emerging AI technologies and continuously improve intelligent solution delivery.
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