data
Posted Mar 31Machine Learning Engineer
at Ventasreit
United StatesHybrid
Responsibilities
- Build and maintain end‑to‑end ML pipelines, including data ingestion, feature engineering, training, evaluation, and inference.
- Implement MLOps best practices, including CI/CD, model versioning, monitoring, and retraining strategies.
- Optimize model performance, scalability, reliability, and cost efficiency in production environments.
- Integrate machine learning models into enterprise applications, APIs, and data platforms.
- Ensure data quality, model explainability, and adherence to security, governance, and compliance standards.
Requirements
- About the Role The Machine Learning Engineer is responsible for designing, building, deploying, and maintaining production‑grade machine learning solutions that drive business value across the enterprise.
- This role sits at the intersection of software engineering and data science, with a strong focus on scalable ML systems, model lifecycle management, and integration with enterprise platforms.
- Responsibilities: responsibilities include: Design, develop, train, and deploy machine learning models using supervised and unsupervised techniques (e.g., regression, classification, clustering, anomaly detection).
- Communicate complex machine learning concepts and results clearly to technical and non‑technical stakeholders.
- Qualifications Bachelor’s degree in Computer Science, Data Science, Engineering, or equivalent experience. 5+ years of
- experience building and deploying machine learning models in production environments.
- Proficiency in Python and
- experience with machine learning frameworks such as TensorFlow, PyTorch, and Scikit‑learn. Strong
- experience with AWS SageMaker for data preparation, pipelines, and model deployment.
- Experience with Git and modern software engineering best practices. Familiarity with SQL (including T‑SQL) and
- experience working with relational and geospatial databases.
- Experience with retrieval‑augmented generation or generative AI solutions is a plus.
- Understanding of Agile development practices and comfortable working in evolving, ambiguous environments.