MLOPS Engineer - Chicago, IL (Hybrid) - Locals only

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 quickly
• Strong expertise in SQL (complex queries, relational databases like PostgreSQL)
• Experience with NoSQL databases: Redis, Elasticsearch
• Hands-on experience with Big Data technologies: EMR, Spark, Kafka/Kinesis
• Deep knowledge of AWS services: Lambda, Glue, Athena, Kinesis, IAM, EMR/PySpark
• Proficient in Docker for containerization
• CI/CD development using Git, Terraform, and Agile methodologies
• Experience with stream-processing systems: Storm, Spark Streaming
• Familiarity with workflow management tools: Airflow
• Experience with ML frameworks: TensorFlow, PyTorch, Scikit-learn, XGBoost
• Model deployment using: Flask, FastAPI, Docker, Kubernetes, TensorFlow Serving, TorchServe

Good to have skills: -

• Exposure to Knowledge Graph Technologies: Graph DB, OWL, SPARQL
• Familiarity with additional programming languages and tools as needed.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.