Scorebuddy Jobs & Careers

Tired of cold applications?

Sign up with Clera and we'll reach out the moment a role actually fits you — no more spraying applications into the void.

Responsibilities

You will build, integrate, and fine-tune LLM pipelines and NLP workflows for production use cases. Additionally, you will collaborate with data scientists to productionise ML models and design scalable backend services.

Requirements

Candidates must have three or more years of professional software engineering experience with strong proficiency in Python and NLP techniques. Practical experience with LLMs, Hugging Face, and AWS cloud infrastructure is required.

Full job description

About Scorebuddy

Scorebuddy is a leading Quality Management SaaS platform for Contact Centres. By combining quality management, coaching and learning with advanced AI Analytics, we help hundreds of customers worldwide to be operationally efficient, scale their contact centres, improve agent performance, and enhance overall customer experience.

We are a globally successful SaaS company, serving a diverse international customer base with teams ranging in size from 20 to 20,000 end users.

Overview
We’re looking for an experienced AI Software Engineer to join our team and help us build the next generation of AI-powered features inside the Scorebuddy platform. You will sit within our AI squad, working alongside engineers who are already shipping production ML and LLM features used by contact centre quality teams around the world.

You will partner closely with product managers, fellow engineers and, in time, the data scientists we plan to bring on board, to shape how AI is applied to real customer conversations. Our stack runs on AWS with Python services driving our NLP and LLM workloads, Go microservices handling high-throughput data ingestion, and we are actively investing in the Hugging Face ecosystem, modern LLM frameworks and retrieval-augmented generation architectures.

This role offers a genuine opportunity to influence how Scorebuddy scales its AI capability over the next phase of growth, from improving the quality and reliability of our production scoring pipelines to introducing new AI-driven features that our customers rely on every day. You will be trusted to make sound technical decisions, ship reliable software and help raise the bar for engineering practice across the team.

Three or more years of professional software engineering experience
Strong proficiency in Python across scripting, data pipelines and ML integration
Hands-on experience with NLP techniques and libraries such as spaCy, NLTK and Hugging Face Transformers
Practical experience working with LLMs across prompt engineering, fine-tuning, RAG architectures or API integration
Proven experience with the Hugging Face ecosystem, including model loading, tokenisation, fine-tuning BERT-family models such as BERT, RoBERTa, DistilBERT, ALBERT and ELECTRA, and publishing or consuming models from the Hugging Face Hub
Solid experience deploying and operating workloads on AWS, covering compute, storage, messaging and managed AI/ML services
Familiarity with containerisation and orchestration tools such as Docker and Kubernetes
Strong understanding of distributed systems, data modelling and API design principles

Nice To Have

Experience in Go, building microservices, REST or gRPC APIs and concurrent systems
Experience with CI/CD pipelines and infrastructure as code such as Terraform or AWS CDK
Experience with vector databases such as Pinecone, Weaviate, pgvector or ChromaDB
Snowflake experience a key plus
Familiarity with streaming data platforms such as Kafka or Kinesis
Contributions to open-source NLP or LLM projects
Experience with model evaluation, observability and LLMOps tooling
Knowledge of ML frameworks such as PyTorch or TensorFlow
Background in building developer tools or internal AI platforms

Education & Qualifications

BSc or MSc in Computer Science, Software Engineering or a related technical discipline, or equivalent practical experience
Build, integrate and fine-tune LLM pipelines for production use cases
Develop and maintain NLP workflows including text classification, entity recognition, summarisation, embeddings and retrieval-augmented generation (RAG)
Train, fine-tune and deploy Hugging Face Transformer models such as BERT, RoBERTa, DistilBERT and ELECTRA for downstream NLP tasks
Collaborate with data scientists to productionise ML models and NLP experiments
Write clean, well-tested and documented code with an emphasis on performance and reliability
Participate in code reviews, system design discussions and on-call rotations
Continuously evaluate and adopt emerging LLM frameworks and tooling such as LangChain, LlamaIndex and the OpenAI and Anthropic APIs
Design and implement scalable backend services and APIs in Python
Competitive salary and performance-based bonus
Hybrid working with modern offices located in Dublin city
25 paid holidays annually
Subsidised gym membership and free on-site gym
Webdoctor online GP service access
Taxsaver tickets & Cycle to Work schemes
Enhanced maternity, paternity and sick leave pay
Access to Irish Life PRSA, salary sacrifice

Related keywords

AI Software EngineerSaaSQuality ManagementNLPLLMPythonGoAWSHugging FaceRAGDockerKubernetesMachine LearningData PipelinesMicroservicesREST API

Jobs at Scorebuddy (Now Hiring) — 3 open

AI Software Engineer

Senior QA Automation Engineer

Software Engineer

AI Software Engineer

Tired of cold applications?

Responsibilities

Requirements

Full job description

Related keywords

About Scorebuddy

About Scorebuddy

Similar companies hiring

Tools

Explore

Platform

Clera

Tools

Explore

Platform

Clera