Middle AI/ML Engineer

About this role

<p>We are looking for a <strong>Middle AI/ML Engineer</strong> to develop and enhance AI-driven solutions within the Palantir Foundry and AIP ecosystem.</p> <p>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.</p> <p><strong>Responsibilities:</strong></p> <ul> <li>Develop and enhance machine learning and AI models to support predictive analytics, classification, forecasting, and AI-assisted workflows.</li> <li>Build AI and ML solutions within <strong>Palantir Foundry</strong>, using Python and existing Foundry pipelines, Ontology objects, and workflows.</li> <li>Apply <strong>LLMs and NLP techniques</strong> (e.g. prompt engineering, fine-tuning, embeddings, retrieval-augmented workflows) using <strong>Palantir AIP</strong> for enterprise use cases.</li> <li>Collaborate with data engineers to understand data sources, ensure data quality, and prepare datasets for model training and inference.</li> <li>Conduct experiments, evaluate model performance, and iterate on features and model approaches.</li> <li>Integrate AI models into Foundry workflows to surface insights and support business processes.</li> <li>Support model deployment and monitoring by following established team standards and best practices.</li> <li>Work closely with business and domain stakeholders to translate requirements into practical AI-driven solutions.</li> <li>Document model behavior, assumptions, and limitations to support transparency and compliance.</li> <li>Stay up to date with applied AI and GenAI trends and contribute ideas under guidance from senior team members.</li> </ul> <p><strong>Requirements:</strong></p> <ul> <li><strong>3+ years</strong> of experience in machine learning, AI engineering, or applied data science.</li> <li>Strong Python skills; experience with ML libraries such as <strong>scikit-learn, XGBoost, TensorFlow, or PyTorch</strong>.</li> <li>Practical experience with <strong>RAG</strong> architectures, vector databases, and retrieval strategies</li> <li>Hands-on experience with <strong>LLMs, NLP, or GenAI use cases</strong> (e.g. prompt design, embeddings, text classification, summarization).</li> <li>Practical understanding of the ML lifecycle: data preparation, feature engineering, model training, evaluation, and iteration.</li> <li>Experience working with structured data (tabular, time series); exposure to text or unstructured data is a plus.</li> <li>Familiarity with enterprise data environments and collaborative development workflows.</li> <li>Ability to clearly explain model results and AI behavior to non-technical stakeholders.</li> <li>Upper-Intermediate English or higher.</li> </ul> <p><strong>Nice to have:&nbsp;</strong></p> <ul> <li>Proficiency in Foundry Ontology, Object Builders, and Code Repositories.</li> <li>Experience in big pharma or highly regulated industries.</li> <li>Knowledge of data privacy, compliance, and security best practices in AI applications.</li> <li>Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).</li> </ul><div class="content-conclusion"><p><strong>We offer*:</strong></p> <ul> <li>Flexible working format - remote, office-based or flexible</li> <li>A competitive salary and good compensation package</li> <li>Personalized career growth</li> <li>Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)</li> <li>Active tech communities with regular knowledge sharing</li> <li>Education reimbursement</li> <li>Memorable anniversary presents</li> <li>Corporate events and team buildings</li> <li>Other location-specific benefits</li> </ul> <p>*not applicable for freelancers</p></div>