Let's build Pyyne together!

Are you excited by the idea of working on cutting-edge technology while shaping the direction of the company you’re part of? At Pyyne, you’ll do both. We're looking for a motivated colleague to join our consultant team who wants to take ownership of their projects and play an active role in building an international, people-first tech consultancy.

About the Role: Consultant at Pyyne

As a consultant at Pyyne, you’ll be embedded in client teams, working on-site or in hybrid setups to deliver high-quality solutions. You’ll have full ownership of your projects and be trusted to collaborate directly with stakeholders to design and implement robust systems.

We work project-based, and that means flexibility, not just in how you work, but in what you work on. You’ll have the freedom to guide your career in the direction that fits your interests and strengths, whether that’s backend development, cloud infrastructure, DevOps, or data engineering.

We're not only building great software; we're also building a great company. Your ideas, your voice, and your initiative will help shape our culture and the way we work.

Responsibilities

• Collaborate closely with client teams to gather requirements and deliver scalable, maintainable solutions
• Take ownership of full project lifecycles, from design to deployment
• Work with modern technologies across backend, cloud, and infrastructure
• Contribute to internal initiatives that improve how we operate as a company
• Mentor others and foster a knowledge-sharing culture

About You

You feel comfortable working with Python and have hands-on experience in developing and deploying machine learning or AI-based systems. You’ve likely worked with some of the following tools and frameworks across the ML lifecycle:

Core Skills

• Strong proficiency in Python for data processing, model development, and automation
• Solid understanding of machine learning fundamentals, model evaluation, and feature engineering
• Experience with end-to-end ML pipelines, from data ingestion to deployment

Frameworks / Platforms

• TensorFlow, PyTorch, or scikit-learn
• LangChain, Hugging Face Transformers, OpenAI API, or other LLM frameworks
• Spark (MLlib), Airflow, MLflow, or Kubeflow for scalable data and model pipelines
• FastAPI or Flask for model serving and API integration
• Docker/Kubernetes and cloud platforms (AWS, GCP, or Azure) for deployment and orchestration
  

Libraries and Tools

• Pandas, NumPy, Dask, PySpark for data handling
• XGBoost, LightGBM, CatBoost for classical ML
• OpenCV for computer vision
• NLTK, SpaCy, Gensim for NLP
• Weights & Biases, Comet, or similar tools for experiment tracking and model monitoring

Bonus Skills

• Experience fine-tuning or serving large language models (LLMs)
• Familiarity with vector databases and retrieval-augmented generation (RAG)
• Knowledge of reinforcement learning or generative AI techniques
• Understanding of MLOps best practices and CI/CD for ML

  
  

Academic Requirements:

A Master’s degree in Computer Science, Engineering, or a related field

Languages:

English - Must Have
Swedish - Good to have

What We Offer

• Competitive salary and pension package
• Stock options
• Health insurance and wellness allowance
• Laptop, phone, and other tools of your choice
• Mentorship program and international career opportunities
• A diverse, inclusive team environment focused on growth and learning

Our Recruitment Process

1. Intro chat – Let’s get to know each other and share what we’re building
2. Technical discussion – A deep dive into your experience (no live coding, tests, or case studies)
3. Values interview – A conversation about how we can shape the right role for you