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Middle AI/ML Engineer

Onsite / UkraineFull timeMid level (2–4 years)
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About the role

We are looking for a Middle AI/ML Engineer to develop and enhance AI-driven solutions within the Palantir Foundry and AIP ecosystem.

In this role, you will focus on building and iterating on machine learning and LLM-based solutions, integrating them into Foundry workflows to support analytics, automation, and decision-making. You will collaborate closely with data engineers, business analysts, and domain experts to deliver practical, production-ready AI solutions.

Responsibilities:

  • Develop and enhance machine learning and AI models to support predictive analytics, classification, forecasting, and AI-assisted workflows.
  • Build AI and ML solutions within Palantir Foundry, using Python and existing Foundry pipelines, Ontology objects, and workflows.
  • Apply LLMs and NLP techniques (e.g. prompt engineering, fine-tuning, embeddings, retrieval-augmented workflows) using Palantir AIP for enterprise use cases.
  • Collaborate with data engineers to understand data sources, ensure data quality, and prepare datasets for model training and inference.
  • Conduct experiments, evaluate model performance, and iterate on features and model approaches.
  • Integrate AI models into Foundry workflows to surface insights and support business processes.
  • Support model deployment and monitoring by following established team standards and best practices.
  • Work closely with business and domain stakeholders to translate requirements into practical AI-driven solutions.
  • Document model behavior, assumptions, and limitations to support transparency and compliance.
  • Stay up to date with applied AI and GenAI trends and contribute ideas under guidance from senior team members

Requirements:

  • 3+ years of experience in machine learning, AI engineering, or applied data science.
  • Strong Python skills; experience with ML libraries such as scikit-learn, XGBoost, TensorFlow, or PyTorch.
  • Practical experience with RAG architectures, vector databases, and retrieval strategies
  • Hands-on experience with LLMs, NLP, or GenAI use cases (e.g. prompt design, embeddings, text classification, summarization).
  • Practical understanding of the ML lifecycle: data preparation, feature engineering, model training, evaluation, and iteration.
  • Experience working with structured data (tabular, time series); exposure to text or unstructured data is a plus.
  • Familiarity with enterprise data environments and collaborative development workflows.
  • Ability to clearly explain model results and AI behavior to non-technical stakeholders.
  • Upper-Intermediate English or higher.

Nice to have: 

  • Proficiency in Foundry Ontology, Object Builders, and Code Repositories.
  • Experience in big pharma or highly regulated industries.
  • Knowledge of data privacy, compliance, and security best practices in AI applications.
  • Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).

We offer*:

  • Flexible working format - remote, office-based or flexible
  • A competitive salary and good compensation package
  • Personalized career growth
  • Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
  • Active tech communities with regular knowledge sharing
  • Education reimbursement
  • Memorable anniversary presents
  • Corporate events and team buildings
  • Other location-specific benefits

*not applicable for freelancers

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