Role overview
Ukraine
What we're looking for
We are looking for a Middle Machine Learning Engineer to develop and enhance AI-driven solutions within the Palantir Foundry and AIP ecosystem.
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.
Strong Python skills; experience with ML libraries such as scikit-learn, XGBoost, TensorFlow, or PyTorch.
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.
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