Role : MLOps Engineer
Location : Chicago, IL (Hybrid) - Locals only
Interview : In-person
Experience : 10+ years
We are seeking a skilled Data & ML Engineer with expertise in Python, AWS, Big Data, and model deployment to build scalable data pipelines and production-ready ML solutions.
Responsibilities : -
- Design, build, and maintain scalable data pipelines and architectures
- Develop and deploy machine learning models in production environments
- Collaborate with cross-functional teams to understand data requirements and deliver solutions
- Optimize performance of data systems and ensure data quality
- Implement CI / CD pipelines and automate deployment processes
- Work with cloud infrastructure and manage resources efficiently
- Stay updated with emerging technologies and contribute to architectural decisions
Educational Qualifications : -
Engineering Degree BE / ME / BTech / MTech / BSc / MSc.Technical certification in multiple technologies is desirable.Mandatory skills
Proficient in Python (must-have) and capable of learning new languages quicklyStrong expertise in SQL (complex queries, relational databases like PostgreSQL)Experience with NoSQL databases : Redis , ElasticsearchHands-on experience with Big Data technologies : EMR , Spark , Kafka / KinesisDeep knowledge of AWS services : Lambda, Glue, Athena, Kinesis, IAM, EMR / PySparkProficient in Docker for containerizationCI / CD development using Git , Terraform , and Agile methodologiesExperience with stream-processing systems : Storm , Spark StreamingFamiliarity with workflow management tools : AirflowExperience with ML frameworks : TensorFlow , PyTorch , Scikit-learn , XGBoostModel deployment using : Flask , FastAPI , Docker , Kubernetes , TensorFlow Serving , TorchServeGood to have skills : -
Exposure to Knowledge Graph Technologies : Graph DB, OWL, SPARQLFamiliarity with additional programming languages and tools as needed.