ai engineer for predictive analytics

The company develops AI-driven solutions within the Palantir Foundry and AIP ecosystem for analytics, automation, and decision-making. Its solutions integrate machine learning and LLM-based capabilities into production workflows.

• Develop and enhance machine learning and AI models for predictive analytics, classification, forecasting, and AI-assisted workflows;
• Build AI and ML solutions within Palantir Foundry using Python, Foundry pipelines, Ontology objects, and workflows;
• Apply LLMs and NLP techniques, including prompt engineering, fine-tuning, embeddings, and retrieval-augmented workflows, using Palantir AIP;
• 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 according to established team standards and best practices;
• Work 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 the guidance of senior team members.

• 3+ Years of experience in machine learning, AI engineering, or applied data science;
• Strong Python skills and 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, including prompt design, embeddings, text classification, or summarization;
• Practical understanding of the ML lifecycle, including data preparation, feature engineering, model training, evaluation, and iteration;
• Experience working with structured data, including tabular and time-series data;
• 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: Experience with 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 AWS, GCP, Azure, Docker, or Kubernetes.

• Flexible working format: remote, office-based, or flexible;
• Competitive salary and good compensation package;
• Personalized career growth;
• Professional development tools, including a mentorship program, tech talks, trainings, and centers of excellence;
• 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.