ML Engineer (AI Chatbots & LLM)
Fully remote ML engineer role building AI chatbots and LLM-powered conversational agents for a product team: designing context-aware assistants, multilingual NLP and RAG/prompt-engineering workflows, and deploying Python-based ML models and REST APIs to production. Sunday-Thursday work week.
- Compensation
- Not disclosed
- Location
- Not listed
- Work setup
- Remote
- Seniority
- Not specified
- Employment
- Full time
- Experience
- 1+ years
- Category
- Ml / AI
- Posted
Skills
Must have
- 3+ years commercial Python development experience, including production-ready applications
- 1+ year hands-on ML in production, preferably NLP or Computer Vision
- Experience developing AI conversational systems, intelligent assistants, or LLM-based applications
- Experience building chatbots that perform actions and execute workflows beyond basic FAQ
- Experience integrating ML models with backend services and deploying AI features to production
- Understanding of end-to-end ML lifecycle from data prep to deployment and monitoring
- Strong Python plus Pandas, NumPy, and SQL for data processing
- Hands-on ML frameworks such as TensorFlow, Keras, or Hugging Face
- Understanding of NLP principles, language models, and modern LLM architectures
- Practical knowledge of prompt engineering, RAG, fine-tuning, and LLM-backend integration
- Experience developing/maintaining REST APIs with versioning, logging, monitoring, error handling
- Understanding of model deployment, inference optimization, and performance monitoring
- Solid knowledge of Git, HTTP/HTTPS, JSON/XML, and TCP/IP basics
- Familiarity with SDLC, code reviews, automated testing, CI/CD
- Ability to evaluate ML model performance and improve quality with measurable results
- Strong analytical thinking and structured problem solving
- Ability to independently investigate challenges and make reasoned technical decisions
- Product-oriented mindset linking ML solutions to UX and business impact
Nice to have
- Experience with PyTorch, SciPy, OpenCV, Matplotlib
- Familiarity with LangChain or LlamaIndex
- Experience with Docker, NoSQL, and vector databases (Weaviate, pgvector, Milvus)
- Basic JavaScript for frontend integration of ML features
- Experience with diffusion image generation models (FLUX, LoRA, inference optimization)
- Knowledge of automated LLM evaluation frameworks and A/B experimentation
- Experience with multimodal AI (text, images, vision-language models)
- Familiarity with ML observability, experiment tracking, model quality monitoring
Full description
We are looking for an experienced Machine Learning Engineer to join a product development team building innovative AI-powered solutions with a strong focus on intelligent automation and natural language technologies.
We are seeking a technically skilled professional with hands-on experience in machine learning, NLP, and LLM-based applications. The role involves developing intelligent conversational systems capable of understanding context, generating natural responses, and performing meaningful actions within a digital product.
You will have the opportunity to work on challenging AI-driven features, contribute to technical decisions, and collaborate with an experienced engineering team to bring advanced machine learning solutions into production.
Key responsibilities
- Design, develop, and improve AI-powered conversational agents capable of maintaining natural, context-aware interactions and executing actions within the product.
- Build intelligent chatbot workflows that support data collection, automated processes, and task execution.
- Develop and enhance multilingual NLP solutions, including context-aware translation systems that preserve meaning, tone, and communication style.
- Experiment with LLM architectures, prompt engineering techniques, retrieval-augmented generation (RAG), and model optimization approaches.
- Develop, test, and deploy machine learning models and AI-powered features into production environments.
- Build and maintain APIs and backend integrations to ensure reliable communication between ML components and application services.
- Manage the ML development lifecycle, including data preparation, experimentation, model evaluation, deployment, monitoring, and continuous improvement.
- Analyze model performance, identify quality issues, and implement improvements to accuracy, response time, and system reliability.
- Collaborate with backend developers, product managers, and other engineering specialists to align AI functionality with product requirements and business objectives.
Requirements
Professional experience:
- At least 3 years of commercial experience in Python development, including building and maintaining production-ready applications.
- At least 1 year of hands-on experience implementing machine learning solutions in production environments, preferably in NLP or Computer Vision.
- Practical experience developing AI-powered conversational systems, intelligent assistants, or LLM-based applications.
- Experience building chatbots capable of performing actions and executing workflows within a product, beyond basic conversational or FAQ functionality.