Machine Learning Engineer

CTG is seeking to fill a Machine Learning Engineer position for our client.

Location: Remote

Duration: 12 months

Duties:

• Build and maintain production-grade data pipelines (batch and streaming) with clear SLAs, retries, idempotency, and automated backfills.
• Integrate and model data across sources by defining schemas, keys, transformations, and curated layers that support analytics and ML consumption.
• Implement data quality, observability, and governance controls, including validation rules, lineage, access controls, and anomaly detection on data freshness and volume.
• Productionize analytics and ML by packaging models, deploying services or jobs, managing versioning, and monitoring drift, performance, and latency.
• Serve trusted data products to consumers via optimized warehouse tables, feature stores, and APIs, ensuring secure access and predictable query performance."

Skills:

• Advanced statistics and ML modeling (hypothesis testing, experimentation, feature engineering, evaluation, calibration).
• Strong SQL/Python for large-scale data wrangling (joins, windows, tuning, cleansing, reconciliation, automated quality checks).
• Data engineering for scalable batch/streaming pipelines (ETL/ELT, CDC, incremental, Airflow/Prefect/Dagster).
• Deep knowledge of modern data platforms (lakehouse/warehouse, S3/ADLS, Snowflake/BigQuery/Redshift, Parquet/Delta/Iceberg, partitioning, access control).
• MLOps deployment with Docker, Kubernetes, CI/CD, MLflow, and end‑to‑end monitoring.

Excellent verbal and written English communication skills and the ability to interact professionally with a diverse group are required.

CTG does not accept unsolicited resumes from headhunters, recruitment agencies, or fee based recruitment services for this role.

To Apply:

To be considered, please apply directly to this requisition using the link provided. Kindly forward this to any other interested parties. Thank you!

The expected base salary for this position ranges from $110,000 to $145,000. Salary offers are based on a wide range of factors including relevant skills, training, experience, education, market factors, and where applicable, licensure or certifications obtained. In addition to salary, a competitive benefit package is also offered.