VentΔs, Inc. is seeking a Machine Learning Engineer to design, build, deploy, and maintain production-grade machine learning solutions that deliver measurable business value across the enterprise. The role will emphasize scalable ML systems, model lifecycle management (MLOps), and integration with enterprise platforms in a hybrid work setup in Chicago, IL.
Role Summary
You will focus on developing and operating end-to-end machine learning capabilities, from data ingestion and feature engineering through training, evaluation, deployment, and ongoing monitoring. Work will include supervised and unsupervised modeling approaches and the implementation of MLOps practices to support reliable, cost-efficient production performance.
Responsibilities
- Design, develop, train, and deploy machine learning models using supervised and unsupervised techniques such as regression, classification, clustering, and anomaly detection.
- Build and maintain end-to-end ML pipelines covering data ingestion, feature engineering, training, evaluation, and inference.
- Collaborate with Data Science, Data Engineering, and business stakeholders to convert requirements into scalable technical solutions.
- Apply MLOps best practices, including CI/CD, model versioning, monitoring, and retraining strategies.
- Improve model performance, scalability, reliability, and cost efficiency for production environments.
- Integrate machine learning models into enterprise applications, APIs, and data platforms.
- Support data quality, model explainability, and adherence to security, governance, and compliance standards.
- Communicate complex machine learning concepts and results clearly to both technical and non-technical audiences.
Requirements
- Bachelorβs degree in Computer Science, Data Science, Engineering, or equivalent experience.
- 5+ years of experience building and deploying machine learning models in production environments.
- Must be located in the Chicago, IL surrounding area or willing to relocate for the duration of employment.
- Ability to thrive in a blended work environment with 3 days in office, with seamless transition between remote work and in-office operations.
- Proficiency in Python and experience with machine learning frameworks including 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 comfort working in evolving, ambiguous environments.
- Legally authorized to work in the United States without employer sponsorship now or in the future.
Technology Stack
- Python
- TensorFlow
- PyTorch
- Scikit-learn
- AWS SageMaker
- Git
- SQL
- T-SQL
Location and Compensation
Location: Chicago, IL (hybrid)
Salary: USD 135,000 - 175,000 per year
Benefits
- Discretionary incentive compensation
- Comprehensive benefits package
- Medical
- Dental
- Vision
- Retirement savings
- Paid time off
- Other wellness benefits under applicable plan terms
