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Machine Learning Engineer

Gdańsk, pomorskie, Poland

Pay
Salary not listed in the saved posting
Work setup
Unconfirmed
Employment
Unconfirmed
Apply at Airspace-Intelligence.com

Tools in this posting

  • Python
  • AWS
  • Kubernetes
  • MLflow
  • PyTorch
  • TensorFlow
  • scikit-learn
Source — Tool mentions in context
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
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:
- 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.

Benefits in the posting

Full benefits wording
  • 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.
  • Generous relocation package to assure smooth relocation to Tricity area.
  • How do we hire:

From the employer’s posting.

About Airspace-Intelligence.com

ASI's mission-critical technology powers decision-making across aviation, defense, energy, and other critical infrastructure domains.

In the employer’s words · Read in context

Job description

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About Air Space Intelligence

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.

How do we hire:

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.

Your next step

  • Have your CV and examples of relevant work ready.
  • Check the listed location, eligibility and core experience before starting.
  • Ask the employer about the salary range before committing time to the process.

Complete your application on jobs.ashbyhq.com. The employer’s form will show what is required.

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Source & posting history

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Pay

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Location & working pattern

Gdańsk, pomorskie, Poland

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Work authorization

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Status in our records
Active
First seen by us
Jun 2, 2026
Recorded sightings
48
Last seen by us
Sep 26, 2026
Employer says posted
Jun 25, 2025

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