Machine Learning Engineer

Air space Intelligence, Inc.

Województwo pomorskie

Hybrid

PLN 180,000 - 280,000

Full time

14 days+
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Benefits offered by this job

Flexible Hours
Healthcare & Insurance
Equity
Relocation package
Energetic environment
Flexible time off
Office equipment
Interview as collaboration

Job summary

Air space Intelligence, Inc. is seeking an experienced machine learning software engineer to design and deploy production-grade ML systems. You will integrate ML models into scalable pipelines, leverage Kubernetes and AWS, and contribute to robust data processing and model governance.

You will work with modern ML tooling, including TensorFlow, PyTorch, and LangChain, and focus on reliable, maintainable software to support critical infrastructure decisions.

Qualifications

  • Proficiency in Python with production ML tooling.
  • Experience deploying ML in production environments (LLMs, prompts, fine-tuning).
  • Strong fundamentals in data structures and software engineering best practices.
  • Knowledge of transformer-based deep learning and MLOps concepts.

Skills

Python
Production ML tooling
LLM in production
Data structures & algorithms
Transformer architectures
MLOps concepts
Distributed systems
Testing pipelines

Tools

TensorFlow
PyTorch
scikit-learn
LangChain
Apache Beam
MLflow

Job description

ASI's mission-critical technology powers decision-making across aviation, defense, energy, and other critical infrastructure domains. Backed by top-tier investors including Andreessen Horowitz, Spark Capital, and Renegade Partners, ASI delivers operational decision superiority—compressing days of analysis into seconds of action. ASI is leading the way and pushing the boundaries of what’s possible.

What you will do:

As part of our core engineering team, you will design and deploy production-grade systems that integrate machine learning models into scalable software pipelines. You’ll develop and ship features that leverage ML to solve real-world optimization and prediction problems, working with modern infrastructure like Kubernetes, AWS, and MLOps tooling. You’ll approach problems with a software engineer’s mindset—prioritizing robustness, maintainability, and performance at scale.

What we value:
  • Proficiency in Python and experience with production ML tooling and frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
  • Experience using LLMs in production environments — covering prompt engineering, fine-tuning, RAG systems, and frameworks like LangChain
  • Strong understanding of data structures, algorithms, and software engineering best practices.
  • Familiarity with classical ML, deep learning with emphasis on transformer architectures, and MLOps concepts.
  • Experience building and maintaining scalable, reliable production ML systems with robust data pipelines, including expertise with Apache Beam, MLflow, and similar production-grade tools.
  • Commitment to high-quality ML engineering practices, including data versioning, experiment tracking, model governance, and automated testing pipelines.
  • A bias for simplicity and clarity in solving complex problems.
  • Intellectual curiosity and willingness to collaborate.
  • Clear communication and collaboration across cross-functional teams.
What we offer:
  • Flexible Working Hours: With a global team supporting mission-critical operations, we have to be at our best, so we’ve adopted flexible hours to allow for balance.
  • Premium Healthcare and Health Insurance: Health and wellness are critical to living a happy and resilient life. We provide first-class medical, dental and vision coverage to you and your dependents.
  • Competitive Salary & Equity: Our team is our biggest asset. We value the hard work that each person commits to us, so we provide competitive, transparent compensation packages.
  • Generous relocation package to assure smooth relocation to Tricity area.
  • High Energy Environment: We live by the mantra that now is better than never. You will find yourself surrounded by peers who constantly challenge the status quo.
  • Flexible Time Off: We encourage you to take time off as you need it. While our team is hard-working, our success is measured by output—not time spent.
  • Office, Equipment & Tools: We bring the best tools to the mission, from ergonomic desk setups to modern productivity software. We have a freshly prepared team breakfast and lunch every day.
  • We look at the interview process not as screening test but rather as an opportunity to simulate what it would look like working together. We build the interview process around you.
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