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ML Engineer (AI Chatbots & LLM)

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Summary

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.

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.

  • Experience integrating ML models with backend services and deploying AI-powered features into production.

  • Understanding of the end-to-end ML development lifecycle, from data preparation and experimentation to deployment and performance monitoring.

Technical skills:

  • Strong proficiency in Python and experience working with Pandas, NumPy, and SQL for data processing and analysis.

  • Hands-on experience with machine learning frameworks such as TensorFlow, Keras, or Hugging Face.

  • Understanding of NLP principles, language models, and modern LLM-based architectures.

  • Practical knowledge of prompt engineering, RAG, fine-tuning approaches, and LLM integration with backend systems.

  • Experience developing and maintaining REST APIs, including API versioning, logging, monitoring, and error handling.

  • Understanding of model deployment, inference optimization, and performance monitoring practices.

  • Solid knowledge of Git, HTTP/HTTPS, JSON/XML, and basic networking concepts (TCP/IP).

  • Familiarity with software development practices, including SDLC, code reviews, automated testing, and CI/CD pipelines.

  • Ability to evaluate ML model performance, identify limitations, and improve solution quality based on measurable results.

Soft skills:

  • Strong analytical thinking and a structured approach to solving complex technical problems.

  • Ability to independently investigate challenges, evaluate alternative solutions, and make well-reasoned technical decisions.

  • Product-oriented mindset with an understanding of how ML solutions impact user experience and business performance.

  • Attention to detail and commitment to delivering reliable, maintainable, and scalable solutions.

  • Strong communication skills and the ability to collaborate effectively with cross-functional engineering and product teams.

Nice to have

  • Experience with additional ML frameworks and libraries, including PyTorch, SciPy, OpenCV, and Matplotlib.

  • Familiarity with LLM application frameworks such as LangChain or LlamaIndex.

  • Experience working with Docker, NoSQL databases, and vector databases such as Weaviate, pgvector, or Milvus.

  • Basic JavaScript knowledge for integrating ML-powered functionality with frontend applications.

  • Experience with diffusion-based image generation models, including FLUX, LoRA, and inference optimization techniques.

  • Knowledge of automated LLM evaluation frameworks, offline/online testing, and A/B experimentation.

  • Experience developing multimodal AI applications involving text, images, or vision-language models.

  • Familiarity with ML observability, experiment tracking, and model quality monitoring tools.

Compensation & Benefits

  • Challenging and engaging projects: the opportunity to contribute to the development of innovative AI-powered features and intelligent automation solutions alongside an experienced technical team.

  • Work format: fully remote, full-time position.

  • Compensation: competitive salary based on experience and technical expertise.

  • Benefits: paid annual leave, paid sick leave, additional paid days off, and public holidays in accordance with the company's internal holiday calendar.

  • Professional development: opportunities to attend relevant courses and training programs funded by the company.

  • Working hours: Sunday to Thursday, 10:00 AM – 7:00 PM (GMT+2 in winter / GMT+3 in summer).

Let's connect!

If you are passionate about machine learning, enjoy building intelligent conversational systems, and want to turn advanced AI technologies into real-world product solutions, we would love to hear from you.

Send us your CV - let's discuss your experience, professional interests, and potential opportunities to work together!

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