Python Engineer — AI Forecasting & Modelling (Energy Markets)
Python Engineer — AI Forecasting & Modelling (Energy Markets)

Python Engineer — AI Forecasting & Modelling (Energy Markets)

Full-Time 60000 - 75000 £ / year (est.) No home office possible
Modo Energy

At a Glance

  • Tasks: Build and maintain backend services for AI-powered energy forecasting models.
  • Company: Modo Energy, a mission-driven startup focused on the energy transition.
  • Benefits: Competitive salary, employee equity, top-tier healthcare, and 25 days annual leave.
  • Other info: Hybrid work environment with excellent career growth opportunities.
  • Why this job: Join a dynamic team shaping the future of energy with cutting-edge technology.
  • Qualifications: 3-5 years Python experience, strong backend skills, and familiarity with Django REST Framework.

The predicted salary is between 60000 - 75000 £ per year.

Modo Energy is building AI-powered tools for understanding global energy markets — combining large-scale data, forecasting models, and LLM systems into high-performance interfaces engineers and analysts use every day. We're hiring a backend Python Engineer to join the Modelling team — the brains behind Modo Energy's forecast product. Our forecasts help investors, operators, and traders understand what energy assets will do next, and they need to be fast, reliable, and trusted.

You'll work across the full backend stack that powers these models: the APIs that serve forecasts to the Terminal, the pipelines that run them at scale, and the infrastructure that keeps everything ticking. You'll work closely with energy analysts and data scientists to turn quantitative models into production-grade systems that customers depend on daily. We’re an AI-native engineering team — everyone uses AI coding tools and many of the systems we build are designed to be consumed by AI agents as much as humans.

What You’ll Do

  • Build and maintain the backend services that run and serve Modo's energy forecasting models — Django REST Framework APIs, Celery task pipelines, and the data layers that connect them.
  • Work directly with data scientists and energy analysts to take new models to production, making sure they run reliably and return results customers can trust.
  • Design and optimise job orchestration for compute-intensive modelling workloads — scheduling, retries, monitoring, and scaling via Celery, AWS, and Airflow.
  • Own AWS infrastructure and deployment across the full lifecycle — local development through to production — using Terraform and Docker.
  • Build monitoring, alerting, and validation tooling to catch model failures and data quality issues before customers do.
  • Own your projects end-to-end, from architecture and design through the full development lifecycle, deploying into a live production environment.

What We’re Looking For

  • Bachelor’s/Master’s degree in Information Technology, Computer Science, or equivalent experience.
  • 3–5 years of Python with strong backend fundamentals — clean, well-structured code, comfortable owning services end-to-end from API design through to deployment and monitoring.
  • Solid experience with Django REST Framework in production.
  • Proficiency with Celery for task orchestration and background processing.
  • Production experience with Docker, AWS, and infrastructure-as-code (Terraform).
  • Strong testing habits — pytest, fixtures, mocking, CI pipelines that actually catch things.
  • Expert-level use of AI coding tools (Claude Code, Cursor, GitHub Copilot, or similar) — knowing when to trust them, when to intervene, and how to get the most out of them.
  • Good taste and judgment — you’ll be making constant decisions about how to structure data pipelines, what to optimise, and when something is ready to ship.

Nice to Have

  • Experience taking quantitative models to production.
  • Familiarity with energy markets.
  • Familiarity with time-series data.
  • Any start-up / scale-up experience is beneficial.

The Company

At Modo Energy, we're on a mission to build the information architecture for the energy transition - we want to be the only place to come to for information on the global journey to net zero. We are looking for individuals who love product-building, want to work with pace at a mission-oriented startup, and will collaborate with us in shaping the culture of a rapidly growing team.

Hybrid Work Environment: This role is hybrid, with time split between working from home and our London office (Euston Square), with in-office days Tuesday, Wednesday and Thursday.

Salary & Benefits

Competitive market rates - we want the best engineers! Employee Equity Scheme. Private Top-Tier Healthcare and Dental coverage with Bupa, a Pension scheme with employer contribution, 25 days of annual leave (excluding bank holidays), 5 flexible days to be taken on a Monday or Friday. And lots of snacks and drinks – obviously!

Python Engineer — AI Forecasting & Modelling (Energy Markets) employer: Modo Energy

Modo Energy is an exceptional employer for Python Engineers, offering a dynamic and mission-driven work environment focused on building AI-powered tools for the energy sector. With a hybrid work model based in London, employees benefit from competitive salaries, equity schemes, comprehensive healthcare, and generous leave policies, all while collaborating closely with a talented team dedicated to innovation and sustainability in energy markets.
Modo Energy

Contact Detail:

Modo Energy Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Python Engineer — AI Forecasting & Modelling (Energy Markets)

Tip Number 1

Network like a pro! Reach out to folks in the energy and AI sectors on LinkedIn or at industry events. A friendly chat can lead to opportunities that aren’t even advertised yet.

Tip Number 2

Show off your skills! Create a GitHub repository with projects that highlight your Python prowess, especially in backend development. This gives potential employers a taste of what you can do.

Tip Number 3

Prepare for those interviews! Brush up on your Django REST Framework and Celery knowledge. We want to see how you think through problems and design solutions, so practice coding challenges too.

Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are genuinely interested in joining Modo Energy.

We think you need these skills to ace Python Engineer — AI Forecasting & Modelling (Energy Markets)

Python
Django REST Framework
Celery
AWS
Terraform
Docker
pytest
CI pipelines
AI coding tools
Data Pipeline Design
Task Orchestration
Monitoring and Alerting
Production Deployment
Problem-Solving Skills
Collaboration with Data Scientists

Some tips for your application 🫡

Tailor Your CV: Make sure your CV is tailored to the Python Engineer role. Highlight your experience with Django REST Framework, Celery, and AWS. We want to see how your skills match what we're looking for!

Showcase Your Projects: Include any relevant projects you've worked on, especially those involving backend services or energy markets. This gives us a glimpse of your hands-on experience and problem-solving skills.

Craft a Compelling Cover Letter: Your cover letter should tell us why you're excited about working at Modo Energy. Share your passion for AI and energy markets, and how you can contribute to our mission. We love a good story!

Apply Through Our Website: Don't forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. We can't wait to hear from you!

How to prepare for a job interview at Modo Energy

Know Your Python Inside Out

Make sure you brush up on your Python skills, especially focusing on backend fundamentals. Be ready to discuss your experience with Django REST Framework and how you've used it in production. Prepare to showcase your clean coding practices and any projects where you've owned services end-to-end.

Familiarise Yourself with AI Tools

Since Modo Energy values AI-native engineering, get comfortable with AI coding tools like GitHub Copilot or Claude Code. Think about specific instances where these tools have helped you in your work, and be prepared to discuss when you trust them versus when you prefer to intervene.

Understand the Energy Market Context

Even if you're not an expert, having a basic understanding of energy markets will set you apart. Research current trends and challenges in the sector, and think about how your role as a Python Engineer can contribute to solving these issues through forecasting models.

Prepare for Technical Challenges

Expect to face technical questions or challenges during the interview. Practice explaining your approach to designing and optimising job orchestration for compute-intensive workloads. Be ready to discuss your experience with AWS, Docker, and Terraform, and how you've used them in past projects.

Python Engineer — AI Forecasting & Modelling (Energy Markets)
Modo Energy

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