Machine Learning Engineering Intern developing innovative AI solutions for contact centers at Cresta. Collaborating with top researchers and engineers in AI to unlock customer experience potential.
About the role
- Lead ML Engineer developing scalable data pipelines and ML systems for Newfold Digital. Collaborate with cross-functional teams using Python, SQL, and cloud ML platforms in an applied ML environment.
Responsibilities
- Partner with the business to translate requirements into clear problem statements, KPIs, and experiment plans (A/B, holdout, backtests)
- Design data & ML architectures on lakehouse /warehouse stacks (e.g., Oracle Exadata, Spark/Databricks; Snowflake / BigQuery /Redshift with open table formats like Iceberg/Delta/Hudi or equivalent)
- Build pipelines for ingestion, feature engineering, and training (batch & streaming) using Python + SQL with orchestration (Airflow/Prefect/Dagster)
- Model using scikit-learn/XGBoost/LightGBM and PyTorch/TensorFlow; manage experiments and lineage
- Serve & operate models on a major cloud ML platform (Azure ML, SageMaker or Vertex AI), with CI/CD, canary/blue-green, and rollback guardrails
- Monitor & improve: implement data/model quality and drift monitoring, alerting, and dashboards; close the loop with BI (Power BI/Tableau/Looker)
- Document & review: author concise design docs and run technical reviews; mentor engineers; champion responsible AI practices
Requirements
- 8+ years in applied ML & data engineering (3+ years leading delivery of production ML systems)
- Python expert with production-grade SQL; strong with pandas/Polars, scikit-learn, and one of: XGBoost/LightGBM
- Fluency in core ML toolkits including TensorFlow, PyTorch, scikit-learn, and familiarity with Hugging Face or equivalent frameworks
- Proven record of constructing and maintaining scalable data pipelines—both batch and streaming—for model training and deployment
- Data platforms: hands-on with one of: Oracle ExaData, Spark/Databricks, or Snowflake, BigQuery/Redshift or equivalent; comfortable with open table formats (Iceberg/Delta/Hudi)
- Orchestration: real projects using one of Airflow, Prefect, or Dagster
- Cloud ML platform: production deployments on one of SageMaker, Vertex AI, or Azure ML (pipelines, endpoints, registries)
- MLOps: CI/CD for ML, experiment tracking, model registry, observability (latency, errors), and data/model drift monitoring
- Communication: ability to frame trade-offs and influence cross-functional partners; crisp writing of design/decision docs
Benefits
- Flexible work arrangements
- Professional development
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
Report this job
Found something wrong with the page? Please let us know by submitting a report below.
MLOps/LLMOps Architect designing AI solutions for a next - gen AI platform in Canada. Collaborating with teams on architecture, deployment, and governance in AI environments.
Staff MLOps Engineer responsible for building infrastructure for AI/ML at NBCUniversal. Managing large media datasets, deploying models, and automating data pipelines.
Deep Learning Engineer at NBCUniversal implementing algorithms in computer vision and graphics. Transforming high dimensional data into high - fidelity content using advanced techniques.
Staff Deep Learning Engineer at NBCUniversal implementing core algorithms for 2D and 3D media datasets. Collaborating with cofounders and deploying large - scale algorithms for high - fidelity content.
Senior Machine Learning Engineer at DraftKings shaping player experiences through machine learning solutions. Leading initiatives to improve engagement and retention via advanced data strategies.
Machine Learning Developer at Rocket Innovation Studio designing frameworks for automated decision - making. Collaborating with data scientists to develop algorithms and hosting trained models into business processes.
MLOps Developer leading major workstreams for AI - enhanced aerial surveillance platforms. Focused on deploying deep learning models and influencing MLOps strategy.
ML Engineer on the Alerts Team developing AI for crisis intelligence. Building and maintaining ML models in a dynamic environment.
Senior Staff Machine Learning Engineer at Workiva defining enterprise - level AI architecture and solutions. Leading technical direction and influencing secure AI platform design across multiple teams.