Snowflake ML Consultant

Snowflake ML Consultant

About Infinite Services

Infinite Services is an IT consulting company specializing in data platforms, cloud technologies, business intelligence, and AI solutions. We work with international clients on complex data and technology projects, helping them turn data into business value.

As our client projects continue to grow, we are looking for experienced Snowflake ML Engineers and Consultants to collaborate with us on client engagements and deliver hands-on workshops and training sessions. We are looking for experts who combine strong technical skills with the ability to share knowledge and help client teams apply new technologies in practice.

What We Are Looking For

We are looking for an experienced Snowflake ML Consultant to lead hands-on workshops for our client’s users, analysts, and data scientists.

We are looking for someone who is not only technically strong but also comfortable working directly with client teams, leading workshops, and transferring knowledge in a practical, hands-on way.

If this sounds like a good match, please share your CV and a short overview of your relevant experience with Snowflake ML, MLOps, and training/workshop delivery.

Project Details

• Duration: first project 2 weeks to 1 month (with the possibility to extend)
• Your availability: min 0.7 FTE (if you are available for 1 FTE, we can utilize that)
• Location: Poland/remote
• Polish language: Strong advantage
• Start: ASAP

Must-Have Skills and Experience

• Strong grasp of core algorithms (regression, tree-based models, gradient boosting, clustering, time series) and the Python ML stack (pandas, scikit-learn, XGBoost/LightGBM, SHAP), ideally applied to banking use cases like credit risk, fraud, and churn.
• Hands-on experience with the full model lifecycle: feature engineering, training, versioning, reproducible pipelines, CI/CD, scheduled inference, and drift monitoring, using tools such as MLflow and Git.
• Experience in implementing MLOps with model retraining workflows and production model serving.
• Proven delivery experience with Snowflake ML, Snowflake Notebooks on Container Runtime, inference services on Snowpark Container Services (SPCS), Feature Store, Model Registry, Experiments, and Model Monitors.
• Understanding of model risk management, explainability, model versioning, observability and lineage, and Snowflake governance (RBAC, masking and row-access policies, Horizon), especially in the context of deploying and running ML models.

Nice-to-Have Skills and Experience

• Experience designing and delivering multi-week, lab-based training for analysts and citizen data scientists, ideally in financial services.
• Experience porting PySpark/Spark MLlib pipelines and Hive/Impala SQL to Snowpark and Snowflake SQL, including the use of the Snowpark Migration Accelerator (SMA).
• Ability to explain the key differences between Snowflake and legacy big data platforms (execution model, compute sizing, UDFs/UDTFs, cost) and provide practical refactoring patterns for feature engineering, training, and batch inference.