Machine Learning Engineer (Conversational AI)

Company Background

The company is a UK-based cloud contact center platform that empowers organizations to connect with their customers more effectively. Known for its scalability, reliability, and compliance-focused features, the platform provides omnichannel communication tools including voice, SMS, email, and social messaging. It serves a wide range of industries, helping businesses improve customer engagement, streamline workflows, and boost agent productivity through advanced automation and AI-driven analytics.

Project Description

Conversational AI project focused on optimizing customer interactions using advanced NLP techniques and AI-driven analytics. This initiative leverages state-of-the-art machine learning models and scalable cloud infrastructure to extract actionable insights from conversational data, enabling businesses to better understand and serve their customers.

Technologies

• Python
• LangChain/LangGraph
• OpenAI API
• Azure Services SDKs
• PyTorch
• Transformers
• BertTopic
• Azure DevOps
• Docker
• App Insights
• MIG

What You'll Do

• Apply theoretical NLP and LLM knowledge to design advanced language understanding components;
• Design and develop robust AI pipelines for key conversational analytics features;
• Optimize ML models and inference pipelines for performance and cost-efficiency;
• Research and integrate state-of-the-art LLM architectures (e.g., BERT, T5, GPT) and methodologies (prompt engineering, embeddings, zero-/few-shot learning);
• Collaborate on the architecture and deployment of AI components using Docker and Azure services;
• Maintain and monitor AI systems;
• Contribute to continuous improvement of model accuracy, latency, and explainability;
• Participate in code reviews, documentation, and team knowledge sharing;

Job Requirements

• 5+ years of experience working as a developer; 
• Solid theoretical foundation in NLP;
• Strong Python skills and experience building NLP/ML pipelines in production environments;
• Experience developing and deploying ML systems in cloud environments (preferably Azure);
• Hands-on experience with containerization (Docker) and orchestration tools;
• Solid understanding of distributed systems and asynchronous messaging (Azure Service Bus);
• Familiarity with CI/CD workflows and version control using Azure DevOps;
• Knowledge of English - from Upper-Intermediate; 

Preferred Qualifications

• Experience optimizing ML systems for cost and performance at scale;
• Familiarity with Azure Cloud Services like Azure Batch, VMs, Blob Storage, Compute Gallery, and App Configuration, etc.;
• Experience with model monitoring, observability, and analytics;
• Background in developing customer-facing or enterprise AI applications;
• Experience with LLM fine-tuning, instruction tuning, RAG and AI-powered chatbots;
• Familiarity with evaluation metrics for generative and classification NLP models;

What Do We Offer

The global benefits package includes:

• Technical and non-technical training for professional and personal growth;
• Internal conferences and meetups to learn from industry experts;
• Support and mentorship from an experienced employee to help you professional grow and development;
• Internal startup incubator;
• Health insurance;
• English courses;
• Sports activities to promote a healthy lifestyle;
• Flexible work options, including remote and hybrid opportunities;
• Referral program for bringing in new talent;
• Work anniversary program and additional vacation days.