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