Nucleus Labs

Our client is a 20-year-old Dublin-based software services company  specializing in custom Learning Management Systems for clients across Europe and the US. Through a joint venture with Nucleus AI, the client is now embedding AI/ML capabilities into its LMS — currently powering a v2→v3 upgrade for the largest remote-online-learning provider in Pennsylvania

You’ll join a mature engineering org with a long-running product, working alongside an AI/ML team brought in via the JV to modernize the platform.
 

Role

We’re looking for a Senior .NET Engineer to take ownership of backend architecture and delivery of high-performance applications. This role is hands-on and requires strong experience in distributed systems, cloud environments, and scalable API design. You’ll work closely with product, architecture, and frontend teams to deliver reliable, secure, and maintainable systems.

ResponsibilitiesBackend Development & Architecture

• Design and build scalable backend services using .NET (Core / Framework).
• Develop RESTful APIs and microservices using ASP.NET Core.
• Apply clean architecture principles and enforce coding standards.
• Ensure systems are performant, secure, and maintainable.

Cloud & Infrastructure

• Build and operate services on Microsoft Azure (App Services, Functions, Azure SQL, AKS).
• Implement CI/CD pipelines (Azure DevOps or GitHub Actions).
• Work with containerized environments (Docker, Kubernetes).
• Ensure system reliability, monitoring, and disaster recovery strategies.

System Integration

• Collaborate with frontend teams (React / Angular / Blazor) on API integration.
• Partner with cross-functional stakeholders to translate business needs into technical solutions.

Code Quality & Performance

• Conduct code reviews and enforce best practices.
• Implement unit and integration testing.
• Monitor, profile, and optimize system performance.

Security & Compliance

• Implement secure authentication and authorization (OAuth, JWT).
• Follow OWASP best practices.
• Ensure data protection and system integrity.

Documentation & Improvement

• Maintain clear technical and architectural documentation.
• Continuously improve system design and development workflows.
• Stay current with .NET and cloud ecosystem developments.

Requirements

• 5+ years experience with .NET (C#).
• Strong experience with ASP.NET Core, Web API, Entity Framework, SQL Server.
• Hands-on experience with Microsoft Azure.
• Experience with CI/CD pipelines and Git.
• Experience with Docker and Kubernetes.
• Strong understanding of SDLC, SOLID, and design patterns.
• Experience with unit testing frameworks (xUnit, NUnit, or MSTest).
• Ability to debug and resolve complex issues.
• Strong communication skills.

Nice to Have

• Experience with frontend frameworks (React, Angular, or Blazor).
• Experience with messaging systems (RabbitMQ, Kafka, Azure Service Bus).
• Familiarity with NoSQL databases (Cosmos DB, MongoDB).
• Azure certifications.
• Experience in legal-tech, fintech, or data-heavy platforms.

What Matters for This Role

• Ownership mindset — ability to take responsibility for systems end-to-end.
• Comfort working in ambiguous, fast-moving environments.
• Strong engineering judgment and pragmatic decision-making.
• Genuine interest in AI-assisted systems and data-driven platforms.

Project Description

A digital health company focused on revolutionizing the pharmacy regulatory market through data-driven innovation and technology. The platform leverages AI/ML to accelerate the approval process of therapeutic products, automate regulatory workflows, and enhance decision intelligence for compliance teams.

Role Overview

We are seeking a highly skilled Lead Machine Learning Engineer to join our cross-functional AI team. You will be responsible for designing, training, and deploying machine learning models that power intelligent automation and decision-support systems across our SaaS platform. This role bridges data science, software engineering, and infrastructure — ensuring that models move from prototype to scalable production systems efficiently and reliably.
 

Key Responsibilities

Model Development & Optimization

• Design, build, and train ML models for classification, NLP, entity extraction, and prediction tasks using modern frameworks (e.g., PyTorch, TensorFlow, scikit-learn).
• Conduct feature engineering, hyperparameter tuning, and model validation using statistical and ML techniques.
• Implement retraining, versioning, and A/B testing strategies to continuously improve model performance.
   

MLOps & Deployment

• Collaborate with DevOps and backend engineers to containerize, deploy, and monitor models in production environments.
• Develop automated data pipelines for training, validation, and inference (Airflow, Kubeflow, MLflow).
• Ensure reproducibility, observability, and CI/CD integration of ML workflows using best practices in MLOps.
   

Data Engineering & Experimentation

• Partner with data engineers to define data ingestion and preprocessing strategies for structured and unstructured datasets.
• Build scalable experimentation frameworks and maintain benchmark datasets for consistent model evaluation.
• Establish and maintain data quality checks, drift detection, and feedback loops from production systems.
   

Collaboration & Impact

• Work closely with product and domain experts to translate business problems into ML tasks with measurable ROI.
• Participate in technical design reviews, code reviews, and cross-functional sprint planning.
• Document methodologies, experiments, and model cards for transparency and compliance (HIPAA, SOC 2, GxP).

Requirements

Experience

• 5+ years of hands-on experience in developing, deploying, and maintaining ML models in production environments.
• Demonstrated success in applying ML/NLP to real-world business problems (healthcare, fintech, or regulated industries preferred).

Technical Skills

• Strong proficiency in Python and core ML/data libraries (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow).
• Experience building and optimizing data pipelines using tools like Airflow, Spark, or Ray.
• Solid understanding of software engineering principles, APIs, and containerization (Docker, Kubernetes).
• Familiarity with cloud services (AWS SageMaker, GCP Vertex AI, or Azure ML).
• Experience with ML lifecycle management tools (MLflow, DVC, Weights & Biases).
• Understanding of data security, governance, and compliance in regulated domains.
   

Soft Skills

• Strong analytical and problem-solving skills with attention to detail.
• Excellent communication skills; able to explain technical concepts to non-technical stakeholders.
• Proven ability to work in collaborative, agile environments.
   

Nice to Have

• Experience in NLP (transformers, embeddings, text summarization, entity recognition).
• Exposure to LLM fine-tuning, prompt engineering, or retrieval-augmented generation (RAG).
• Familiarity with healthcare data standards (FHIR, HL7) or claims processing workflows.
• Contributions to open-source ML projects or published research.

What Success Looks Like (First 90 Days)

• Deliver a trained and validated ML model integrated into one production feature.
• Establish an end-to-end retraining pipeline with automated evaluation and version tracking.
• Deploy monitoring and alerting for model drift and performance degradation.
• Contribute to the team’s internal ML standards and reusable templates for experimentation and deployment.

We’re looking for a hands-on SMM / Content Marketing Specialist to help us build and grow the marketing function from the ground up.

We’re an AI product company with a service component, focused on simplifying complex workflows and helping people make better decisions.

If you enjoy building things from zero, creating content, and experimenting — this role is for you.

What You’ll Do

• Create and publish content across social platforms (short-form videos, posts, etc.)
• Translate complex ideas into simple, engaging messaging
• Support growth initiatives and help attract early users
• Drive community growth by bringing users from social platforms into channels like Discord (for one of our products) and similar communities
• Build and maintain consistent company presence online
• Research what resonates with the target audience and use those insights to shape content
• Experiment with content formats and continuously refine based on performance
• Take a data-driven approach: analyze results, identify what works/doesn’t, and iterate quickly
• Manage your own workflow from idea → creation → publishing

What We’re Looking For

• 2+ years of experience in SMM, content, or digital marketing
• Strong execution mindset — you create, not just plan
• Ability to simplify complex topics into clear content
• Strong curiosity and research mindset — you actively look for what works and why
• Analytical thinking — comfortable reviewing performance and improving based on data
• Comfortable working independently and managing your own priorities
• Proactive, ownership-driven, and willing to learn new domains

Nice to Have

• Experience with short-form video content
• Familiarity with tools like CapCut, Canva, or similar
• Experience in startups or fast-paced environments
• Interest in AI, tech, or building products
• Experience building or managing online communities (e.g., Discord, forums)

Important

• This is a hands-on role — you’ll be creating content yourself
• You’ll be the first/only marketing person initially
• As the company grows, we plan to expand the marketing team and add supporting roles, with the opportunity for you to help shape and influence that growth
• We value speed, ownership, and experimentation

Why Join Us

• Opportunity to build marketing from scratch
• Work directly with founders and shape direction
• High ownership and real impact
• Flexible, fast-moving environment

We are seeking a highly skilled and experienced Python Engineer to join our dynamic team. In this role, you will support the development of our backend systems, working closely with cross-functional teams to build and maintain scalable, robust, and secure applications. As a key member of our engineering team, you will be instrumental in shaping the future of our platform, driving innovation, and ensuring the highest standards of software quality.

Key Responsibilities:

• Architectural Design: Support the implementation of a scalable and efficient backend architectures that support the rapid growth and evolution of our platform.
• Development: Write clean, maintainable, and efficient code in Python, ensuring that it meets the needs of our users and aligns with our technical vision.
• Collaboration: Work closely with product managers, front-end developers, and other stakeholders to translate business requirements into technical solutions.
• Performance Optimization: Identify and address performance bottlenecks, optimizing the platform for speed and scalability.
• Security: Implement robust security measures to protect user data and ensure the platform meets the highest security standards.
• Continuous Improvement: Stay up-to-date with the latest industry trends and technologies, continuously improving the development process and tools.

Qualifications:

• Experience: Minimum of 5+ years of professional experience in Python development, with at least 3 years in a senior engineering role.
• Modern AI tools: Excel at usage of the modern tools akin to Cursor, CC, and others. Proven experience in writing agents for tasks.
• Technical Expertise: Strong knowledge of Python and related frameworks (e.g., Django, Flask) with a deep understanding of web development principles.
• Architecture: Proven experience in designing and implementing scalable and distributed systems.
• Database Proficiency: Expertise in working with databases such as PostgreSQL, MySQL, or MongoDB, including experience with ORM frameworks.
• DevOps & CI/CD: Familiarity with DevOps practices, including CI/CD pipelines, containerization (Docker), and cloud platforms (AWS, Azure, GCP).
• Testing: Strong emphasis on testing (unit, integration, and end-to-end) and experience with testing frameworks (e.g., PyTest).
• Communication: Excellent communication skills, with the ability to articulate technical concepts to both technical and non-technical stakeholders.

Nice to Have:

• Knowledge of front-end technologies such as JavaScript, React, or Angular.
• Experience with microservices architecture and RESTful API development.

Project

Our client is a 20-year-old Dublin-based software services company specializing in custom Learning Management Systems for clients across Europe and the US. Through a joint venture with Nucleus Labs, the client is now embedding AI/ML capabilities into its LMS — currently powering a v2→v3 upgrade for the largest remote-online-learning provider in Pennsylvania.

Role

We're looking for a hands-on Fullstack QA Engineer who can operate comfortably as a manual tester and build/maintain automated suites using modern agentic AI practices to deliver fast, reliable regression and release confidence. You'll collaborate closely with Product and Engineering, shaping test strategy, hardening quality gates, and raising the bar on reliability in a regulated domain.

Responsibilities

Test Strategy & Planning

• Translate requirements and acceptance criteria into risk-based test plans and coverage maps across UI, API, data, and integrations.
• Define and evolve a pragmatic test pyramid (unit → API → UI; smoke/sanity, regression, UAT).

Manual Testing

• Create and execute test cases for new features, bug fixes, and change requests; perform exploratory testing to uncover edge cases.
• Log high-quality defects with clear reproduction steps, impact, and evidence; drive resolution with developers.

Test Automation (agentic-AI-first)

• Build and maintain stable, reusable automated suites for smoke and regression using modern agentic AI practices; leverage data-driven and keyword/NLP tests.
• Integrate automation into CI/CD (e.g., GitLab / GitHub Actions) with environment tagging, parallelization, and results gating.
• Expand coverage to API (REST / GraphQL) and key workflows; use custom functions when needed.

Quality Operations

• Own test data management and environment readiness; contribute to mock/stub strategies for external services.
• Track and report quality KPIs (defect escape rate, flaky test rate, regression coverage, cycle time to fix).
• Maintain living documentation (test plans, suites, runbooks, reports) in tools like TestRail / Zephyr.

Collaboration & Process

• Partner with Product for clear acceptance criteria; participate in backlog grooming, design reviews, and release readiness.
• Coach teammates on writing testable stories and preventing regressions ("shift-left" mindset).
• Continuously improve test effectiveness and execution speed; reduce flakiness and manual repetition.

Requirements

• 4–6+ years of QA experience testing SaaS / web applications, including significant hands-on manual testing.
• 2+ years building and maintaining automation for UI and/or API — ideally leveraging modern agentic AI practices (and/or tools like Playwright / Cypress / Selenium, Postman).
• Strong grasp of testing methodologies (functional, regression, smoke/sanity, exploratory, risk-based), and test case design (boundary, equivalence partitioning).
• Experience with bug tracking and test management (e.g., Jira, TestRail / Zephyr) and CI/CD-triggered test runs.
• Comfortable validating web technologies (HTML / CSS / JavaScript), browser devtools, and basic SQL / log analysis for root cause clues.
• Clear, concise communicator with a bias for evidence (screenshots, HAR files, logs) and reproducibility.
• Familiarity with Agile practices (Scrum / Kanban) and working in fast-paced, iterative delivery.

Nice to Have

• Power-user experience with modern agentic AI practices for QA: prompt design, evaluation harnesses, data sets, environments, custom functions, CI artifacts, reporting dashboards.
• API testing depth (Postman / Insomnia / newman) and contract testing basics.
• Exposure to regulated environments (e.g., GxP / 21 CFR Part 11, audit trails, e-signatures) and documentation rigor.
• Basic performance and reliability testing (e.g., k6 / JMeter smoke) and accessibility testing familiarity.
• Experience testing AI/ML features (curated test sets, evaluation harnesses, prompt/response validation, guardrails).

If you're equal parts careful tester and pragmatic automator — and you enjoy making complex, regulated workflows feel rock-solid for users — we'd love to talk.