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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.
Job Responsibility:
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
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)
What 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