Machine Learning Engineer (ML Ops & Computer Vision)

This Position Is Closed

Machine Learning, ML Ops, Palantir Foundry, Computer Vision, Docker, PyTorch, TensorFlow, Keras, Python, NumPy, Pandas, Scikit-learn, AWS, Azure, SQL.

Location:
On-site
Kyiv, Ukraine 🇺🇦

Role Overview

We are seeking a highly technical Machine Learning Engineer to work onsite with a client team in Kyiv, supporting multiple customers and delivering production-grade ML solutions.

This role has a strong emphasis on ML Ops, model deployment, and computer vision, with additional exposure to Palantir Foundry (pipelines and UI). The successful candidate will be comfortable working independently in environments with uncertain or evolving requirements, while collaborating closely with both onsite and remote teams.

Who are we looking for?

Key Responsibilities

  • Design, develop, train, fine-tune, and deploy machine learning models into production environments.
  • Build and maintain ML Ops pipelines, including model versioning, deployment, monitoring, and retraining.
  • Develop and support computer vision solutions for real-world business use cases.
  • Work with structured and unstructured data to deliver scalable ML solutions from PoC → MVP → Production.
  • Use Docker to containerize ML workloads and ensure portability and reproducibility.
  • Contribute to and maintain Palantir Foundry pipelines and UI components (prior experience strongly preferred; training can be provided).
  • Collaborate with cross-functional teams (engineering, product, client stakeholders) both onsite and remotely.
  • Clearly communicate technical approaches, trade-offs, and results to non-technical stakeholders.
  • Proactively drive progress and decision-making, even when requirements are ambiguous.
  • Analyze data to find patterns and create machine learning solutions for challenging business issues
  • Understand the AI/ML program journey to formulate relevant high impact business questions that can be answered through data analysis.

Required Skills & Experience 

  • 3+ years of hands-on experience in Machine Learning, including model training, fine-tuning, and deployment, production ML systems
  • Strong experience with Docker for ML workloads.
  • Proficient with ML Ops concepts (CI/CD for ML, model lifecycle management, monitoring).
  • Hands-on experience with PyTorch, TensorFlow, Keras, advanced Python skills (NumPy, Pandas, Scikit-learn, etc.).
  • Experience working with cloud platforms (AWS, Azure, or similar).
  • Familiarity with SQL for data analysis.
  • Ability to work independently and take ownership of delivery.
  • Fluency in English (spoken and written).
  • Strong interpersonal skills with the ability to translate client requests into technical solutions and explain complex ML topics succinctly to technical and non-technical audiences

Strongly Preferred / Nice to Have

  • Prior experience with Palantir Foundry:Data pipelines, Foundry applications / UI
  • Experience with computer vision use cases.
  • Experience working in agile delivery environments.

What we offer

Work:

  • Flexible working hours;
  • Collaborative, friendly team environment;
  • Remote/Hybrid work;

Life:

  • Company social events;
  • Annual corporate parties;

Health:

  • Comprehensive medical insurance;

Education:

  • Allowances for professional education;
  • English language courses with native speakers;
  • Internal knowledge-sharing sessions.

What we offer

About Proxet

Proxet is a professional software development firm trusted by clients from around the world. With our expertise in AI and machine learning, we help businesses reimagine their possibilities and transform ideas into tangible digital solutions. By providing core services with an emphasis on data practices, we shape the future, one step at a time.

If you’d like to join our Proxet Nation and work closely with high-level professionals and our engineers, fill in the form!

RECRUITER:

Bohdan Hodovaniuk

Interested? Let's get in touch!

Tell us about yourself, then leave a link or upload your resume and we will get back to you soon!

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Interested in this closed position? Let's get in touch!

Tell us about yourself, then leave a link or upload your resume and we will get back to you soon!

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