Description
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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