Middle AI/ML Engineer

Навыки

• AI-инструменты в работе
• AWS
• Azure
• Big Data
• XGBoost / LightGBM / CatBoost
• Data Quality
• Docker

О компании и продукте

• We are looking for a Middle AI/ML Engineer to develop and enhance AI-driven solutions within the Palantir Foundry and AIP ecosystem

Задачи

• 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
• 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
• Middle AI/ML Engineer (#4460257101) - Office/Remote | N-iX
• Search Job
• Middle AI/ML Engineer
• Middle AI/ML Engineer (#5128)
• Europe, Ukraine
• Work type
• Office/Remote
• Technical Level
• Job Category
• Software Development
• Global biopharmaceutical company
• 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

Требования

• 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

Будет плюсом

• 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)
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