Middle ML/AI Engineer

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.

Key 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.


• 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