Machine Learning Engineer
Hybrid in Bloomington, IL, US • Posted 2 days ago • Updated 2 days ago
GNRSystems
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Job Details
Skills
- Amazon SageMaker
- Amazon Web Services
- Analytics
- Apache Spark
- Cloud Computing
- Conflict Resolution
- Continuous Delivery
- Continuous Integration
- Data Flow
- Data Validation
- Debugging
- Deep Learning
- DevOps
- Distributed Computing
- Docker
- Extraction
- Good Clinical Practice
- Google Cloud Platform
- IaaS
- Information Design
- Kubernetes
- Lifecycle Management
- Machine Learning (ML)
- Machine Learning Operations (ML Ops)
- Management
- Microsoft Azure
- Natural Language Processing
- NoSQL
- Problem Solving
- PyTorch
- Python
- Real-time
- SQL
- Storage
- TensorFlow
- Testing
- Time Series
- Training
- Unsupervised Learning
- XGBoost
- scikit-learn
Summary
We are seeking an experienced Machine Learning Engineer to design, develop, and deploy scalable ML models and data pipelines for enterprise-grade analytics platforms. The ideal candidate has a strong background in applied machine learning, model lifecycle management, cloud services, and production deployment.
Responsibilities
Develop, train, and optimize ML models for supervised and unsupervised learning use cases
Build scalable data pipelines for feature extraction, transformation, and orchestration
Deploy ML models into production using CI/CD and model serving frameworks
Monitor model performance, drift, and re-training cycles
Collaborate with data scientists, data engineers, and DevOps teams
Perform feature engineering, data validation, and model evaluations
Implement ML frameworks, libraries, and distributed training solutions
Work with cloud infrastructure for storage, compute, and deployment (AWS, Google Cloud Platform, Azure)
Document design, architecture, data flow, and production workflows
Required Skills & Experience
3+ years hands-on experience as Machine Learning Engineer or similar role
Strong expertise with Python and ML libraries (TensorFlow, PyTorch, Scikit-learn, XGBoost)
Experience with NLP, Time Series, Deep Learning, or Statistical Modeling
Experience with distributed computing (Spark, Dask, Ray or similar)
Familiarity with CI/CD pipelines and containerization (Docker, Kubernetes)
Knowledge of cloud services (AWS preferred, Azure or Google Cloud Platform acceptable)
Experience working with SQL and NoSQL data stores
Excellent problem solving and debugging skills
Preferred Skills
Experience with MLOps, MLFlow, SageMaker, Kubeflow, or Airflow
Model monitoring & observability frameworks
A/B testing or experimentation frameworks
Experience with real-time inference / microservices
Education
Bachelor s degree in Computer Science, Data Science, Engineering, Mathematics, or related technical field (Master s preferred)
- Dice Id: 10524228
- Position Id: 8865753
- Posted 2 days ago
Company Info
GNRSystems is geared to meet today's most demanding and challenging needs of Information Technology Industry. The key focus of our company is to provide cutting edge I/T business solutions using latest technologies, highly skilled professionals, with continuous quality focus, and more importantly at an affordable cost to our client.
We are specialized as a talent management organization with a focus on the placement of technologists through contract, contract-to-hire and permanent placements through our network of 5 regional offices across the U.S. and India. From entry level to highly specialized positions, we take the necessary time to fully understand what both the client and candidate are looking for to ensure a perfect match every time. We believe that quality, integrity, responsiveness and customer service are the cornerstones for a successful partnership with a recruiting firm, so we've laid that as the groundwork for a company.
We believe that finding the right candidate shouldn’t be so hard. Neither should finding a job you love. By taking the time to understand your specific needs, we make the perfect placements and build relationships that last long after the position is filled. We’re fanatical about the right fit, and we look forward to finding yours.
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