Middle/Senior ML/MLOps Engineer (#4672)

N-iX is looking for a Senior Machine Learning Engineer in Kyiv. You will be responsible for designing, developing, and deploying machine learning models at scale within the Palantir Foundry ecosystem. You will collaborate closely with data scientists, MLOps engineers, and data engineers to build robust, production-grade ML workflows—from data preparation and feature engineering to model training, evaluation, deployment, and monitoring.

Key Responsibilities

• 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.

Must-Have Skills & Experience

• 3+ 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.

Will be a plus:

• Experience with Palantir Foundry.