Senior ML/MLOps Engineer

• Design and implement scalable ML models for use in predictive analytics, forecasting, and classification tasks
• Work with Palantir Foundry to build end-to-end ML pipelines, including custom Python code, Foundry Functions, and Ontology-aware feature generation
• Collaborate with Data Engineers to ensure high-quality, model-ready data flows from ingestion to inference
• Operationalize models using industry best practices for versioning, reproducibility, and monitoring (e.g., via MLflow or native Foundry tools)
• Contribute to MLOps automation, including CI/CD for ML, drift detection, retraining pipelines, and evaluation dashboards
• Partner with business stakeholders and domain experts to translate scientific or commercial hypotheses into model-based solutions
• Apply rigorous experimentation and statistical validation to ensure models are explainable, generalizable, and regulatory-compliant
• Stay informed on the latest developments in ML/AI and proactively introduce innovative techniques and frameworks

• 5+ years of experience in machine learning or applied data science, ideally in a production or enterprise setting
• Strong programming skills in Python, with deep experience in machine learning libraries such as scikit-learn, XGBoost, TensorFlow, or PyTorch
• Experience designing and deploying ML workflows at scale, preferably with experience in Foundry, KubeFlow, SageMaker, or similar platforms
• Familiarity with feature engineering, data imputation, sampling strategies, and evaluation techniques
• Hands-on experience with model deployment and monitoring, including logging metrics, detecting drift, and managing model lifecycles
• Comfort working with structured and unstructured data: tabular, time series, text, etc.
• Solid understanding of data security, privacy, and compliance
• Strong communication and stakeholder engagement skills
• capable of explaining complex models in simple terms
• English level at least Upper-Intermediate

Experience with Palantir Foundry

• 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