Middle AI/ML Engineer

Job description

Work type: Office/Remote Technical Level: Middle Job Category: Software Development Project: Global biopharmaceutical company 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