Nucleus

We are seeking a highly capable Full Stack Engineer with deep experience in Python and React, who thrives on harness engineering—building the automation, testing scaffolding, execution environments, and orchestration layers that allow experimental prototypes to evolve into stable, production-ready MVPs.

This role is ideal for engineers who can fluidly move between backend services, frontend product development, integration tooling, and developer platforms. You’ll help transform early-stage prototypes into systems that are testable, observable, repeatable, and reliable at small-to-medium scale.

At this position, your work directly contributes to rapid experimentation: turning concepts built by the founder into scalable, deployable software.

Key Responsibilities

• Build and maintain full stack applications using Python on the backend and React on the frontend. 
• Design and implement APIs, services, and orchestration layers to support product workflows and internal tooling. 
• Develop harnesses for testing, simulation, validation, execution, and monitoring of complex workflows and agent-based systems. 
• Create reusable frameworks for:
• workflow execution
• automated test runs
• sandboxed environments
• synthetic data generation
• scenario replay
• regression validation
• Build developer-facing tools to improve engineering velocity, reliability, and repeatability. 
• Integrate external APIs, services, and third-party tools into internal platforms.
• Implement logging, tracing, observability, and error handling across systems.
• Collaborate with product, design, and platform stakeholders to turn experimental ideas into scalable technical solutions.
• Help define engineering standards for reliability, maintainability, and deployment readiness.

Required Qualifications

• Hands-on experience building production systems with Python. 
• Hands-on experience building modern frontend applications with React. 
• Experience designing and consuming REST APIs and/or async service architectures.
• Demonstrated experience in harness engineering: building tools for testing, validation, simulation, automation, or execution environments.
• Comfortable working across both application code and engineering infrastructure/tooling.
• Strong understanding of software design, debugging, and performance optimization.
• Experience with relational databases such as PostgreSQL, MySQL, or similar.
• Familiarity with CI/CD pipelines, Git-based workflows, and deployment practices.
• Ability to work independently, move quickly, and make sound engineering tradeoffs.

Preferred Qualifications

• Experience with workflow orchestration, agent-based systems, or automation pipelines.
• Experience with Docker, cloud infrastructure, and containerized environments.
• Familiarity with background job systems, queues, and event-driven architectures.
• Experience building internal platforms, QA tooling, evaluation frameworks, or developer productivity tools.
• Exposure to LLM/AI workflow orchestration, RPA, or test automation systems.
• Experience with observability tools, telemetry, and production monitoring.

What Success Looks Like

• You can ship polished frontend and backend features end-to-end. 
• You can build robust harnesses that make systems easier to test, measure, debug, and scale.
• You improve both product delivery and engineering leverage.
• You help the team move faster by making complex workflows repeatable and reliable.

Ideal Candidate Profile

You are more than a feature engineer; you think in systems and ask:
- How do we test this?
- How do we simulate this?
- How do we validate edge cases?
- How do we make this reproducible?
- How do we instrument this so it can be trusted in production?

You enjoy building the glue, scaffolding, and runtime support that transform experimental ideas into dependable products.  

Role Overview
We are looking for a highly capable Full Stack Engineer with deep experience in Python and React who is also very comfortable with harness engineering—building the surrounding tooling, automation, testing scaffolding, execution environments, and orchestration layers that allow systems, agents, workflows, and product features to be developed, validated, and run reliably at scale.

This role is ideal for an engineer who can move fluidly between backend services, frontend product development, automation frameworks, integration layers, and developer tooling. You should be equally comfortable shipping user-facing features and building the technical harnesses that make systems testable, observable, repeatable, and production-ready.

Key Responsibilities

• Build and maintain full stack applications using Python on the backend and React on the frontend.
• Design and implement APIs, services, and orchestration layers for product workflows and internal tools.
• Develop harnesses for testing, simulation, validation, execution, and monitoring of complex workflows, agents, or integrations.
• Create reusable frameworks for:
  • workflow execution
  • automated test runs
  • sandboxed environments
  • synthetic data generation
  • scenario replay
  • regression validation
• Build developer-facing tools to improve engineering velocity, quality, and repeatability.
• Integrate external services, APIs, and third-party tools into internal platforms.
• Implement logging, tracing, observability, and error-handling across systems.
• Collaborate with product, design, and platform stakeholders to turn business needs into scalable technical solutions.
• Help define engineering standards for reliability, maintainability, and deployment readiness.

Required Qualifications

• Strong hands-on experience building production systems with Python.
• Strong hands-on experience building modern frontend applications with React.
• Experience designing and consuming REST APIs and/or async service architectures.
• Experience with harness engineering, including building tooling for testing, validation, simulation, automation, or execution environments.
• Comfortable working across both application code and engineering infrastructure/tooling.
• Strong understanding of software design, debugging, and performance optimization.
• Experience with databases such as PostgreSQL, MySQL, or similar.
• Familiarity with CI/CD pipelines, Git-based workflows, and deployment practices.
• Ability to work independently, move quickly, and make sound engineering tradeoffs.

Preferred Qualifications

• Experience with workflow orchestration, agent-based systems, or automation pipelines.
• Experience with Docker, cloud infrastructure, and containerized environments.
• Familiarity with background job systems, queues, and event-driven architectures.
• Experience building internal platforms, QA tooling, evaluation frameworks, or developer productivity tools.
• Exposure to LLM/AI workflow orchestration, RPA, or test automation systems.
• Experience with observability tools, telemetry, and production monitoring.

What Success Looks Like

• You can ship polished frontend and backend features end-to-end.
• You can build robust harnesses that make systems easier to test, measure, debug, and scale.
• You improve both product delivery and engineering leverage.
• You help the team move faster by making complex workflows repeatable and reliable.

Ideal Candidate Profile
You are not just a feature engineer. You think in systems. You naturally ask:

• How do we test this?
• How do we simulate this?
• How do we validate edge cases?
• How do we make this reproducible?
• How do we instrument this so we can trust it in production?

You enjoy building the “glue,” scaffolding, and runtime support that turn promising ideas into dependable products.

Role Overview

We are looking for an SMM / Content Marketing Specialist who can:

• Create and execute basic social media strategy
• Produce and edit short-form videos
• Manage content publishing and consistency
• Support audience growth and engagement

This is an execution-focused role with light strategic responsibility.

Key Responsibilities

• Develop a simple monthly content plan
• Create short-form videos (2–4 per week)
• Write captions and educational posts
• Edit videos (Reels, Shorts, TikTok format)
• Publish content across platforms (YouTube, X, LinkedIn, etc.)
• Monitor basic metrics (views, engagement, clicks)
• Suggest simple improvements based on performance
• Maintain consistent brand tone and visual style

Requirements

Hard Skills

• (1–3 years) experience in SMM or content creation
• Experience recording and editing short videos
• Basic understanding of content strategy
• Familiarity with video editing tools (CapCut, InShot, etc.)
• Basic analytics understanding

Soft Skills

• Organized and deadline-oriented
• Self-managed and proactive
• Clear written communication
• Willing to test and improve content ideas

What We Offer

• Remote work format
• Opportunity to grow into a broader marketing role
• Competitive compensation (discussed individually)

Role Overview

Nucleus AI is seeking an AI / ML Data Scientist to help build and scale an AI-backed Learning Management System (LMS) that delivers personalized, adaptive learning experiences.

This is a hands-on, product-focused role at the intersection of machine learning, data science, and learning technology. You will design and deploy intelligent systems that directly impact learner engagement, personalization, assessment, and outcomes.

If you enjoy turning real-world data into models that are used by real users—and iterating on them in production—this role is for you.

Key Responsibilities

Machine Learning & Modeling

• Design, develop, and deploy machine learning models that power:
  • Personalized learning paths
  • Content and course recommendations
  • Learner analytics and insights
  • Adaptive assessments and feedback
     
• Build models for:
  • Learner skill inference and knowledge tracing
  • Engagement, completion, and drop-off prediction
  • Automated assessment scoring and feedback
     

Data & Analytics

• Analyze large-scale learner behavior data to extract actionable insights
• Develop and maintain data pipelines, feature engineering workflows, and model evaluation frameworks
• Apply statistical analysis and experimentation (including A/B testing) to validate model performance and impact
   

Collaboration & Product Integration

• Work closely with product managers, engineers, and instructional designers to translate learning objectives into AI-driven solutions
• Integrate models into production systems via APIs, batch pipelines, or real-time inference
   

LLMs & Advanced Techniques

• Experiment with and integrate LLMs and NLP techniques for:
  • Content generation
  • Learner feedback
  • Intelligent learner support
     
• Monitor models in production for performance, bias, and drift, and continuously improve them
   

Documentation & Governance

• Document models, assumptions, experiments, and results to ensure transparency, reproducibility, and maintainability
   

Required Qualifications

• Bachelor’s or Master’s degree in Data Science, Computer Science, AI/ML, Statistics, or a related field
• Strong proficiency in Python and common ML libraries (e.g., scikit-learn, PyTorch)
• Solid understanding of:
  • Supervised and unsupervised learning
  • Feature engineering and model evaluation
  • Statistical analysis and experimentation
     
• Experience working with both structured and unstructured data
• Proficiency in SQL and working with large datasets
• Ability to clearly communicate complex technical concepts to non-technical stakeholders
   

Nice-to-Have Qualifications

• Experience building ML systems in ed-tech, LMS platforms, or learning analytics
• Familiarity with
  • Large Language Models (LLMs)
  • NLP
  • Recommendation systems
  • Knowledge graphs
• Experience deploying models to production environments
• Exposure to cloud platforms such as AWS, GCP, or Azure
• Understanding of learning science, instructional design, or assessment theory
• Experience with MLOps tools (model versioning, monitoring, CI/CD for ML)
   

What We Offer

• Opportunity to work on mission-driven AI that improves how people learn
• Ownership of ML systems used by real learners at scale
• A collaborative, cross-functional team culture
• Competitive compensation and benefits
• Flexible work location and schedule
• Continuous learning and professional growth opportunities