Cymetrix Software - Machine Learning Engineer - Python/ETL

We are looking for a skilled Machine Learning Engineer with expertise in AWS to design, build, and deploy scalable machine learning solutions. The ideal candidate will have a strong background in ML model development, cloud deployment, and data engineering. You will collaborate closely with data scientists, software engineers, and product teams to bring advanced ML-driven features into production systems.

Key Responsibilities :

- Design, develop, and deploy machine learning models and pipelines on AWS cloud services.

- Work with large datasets to perform data cleaning, preprocessing, and feature engineering.

- Implement end-to-end ML lifecycle including model training, validation, deployment, and monitoring.

- Leverage AWS services such as SageMaker, Lambda, EC2, S3, Glue, EMR, and Redshift for ML solutions.

- Optimize ML models for performance, scalability, and cost-efficiency in cloud environments.

- Collaborate with data scientists to transition prototypes into production-grade solutions.

- Build APIs and integrations to make ML models consumable for applications and business workflows.

- Establish monitoring and logging for deployed ML models to ensure reliability and performance.

- Stay updated with the latest ML frameworks, AWS services, and industry best practices.

Required Qualifications & Skills :

- Bachelors/Masters degree in Computer Science, Data Science, AI/ML, or related field.

- 3 to 6 years of experience in machine learning engineering or applied ML.

- Strong programming skills in Python (NumPy, Pandas, Scikit-learn, PyTorch, TensorFlow).

- Hands-on expertise in AWS cloud services (SageMaker, S3, Lambda, Glue, EMR, Redshift, ECS/EKS).

- Solid understanding of data pipelines, ETL processes, and big data technologies.

- Experience with CI/CD for ML (MLOps) using AWS tools or alternatives.

- Familiarity with containerization tools (Docker, Kubernetes) for ML deployment.

- Strong knowledge of API development (REST, Flask, FastAPI).

- Excellent problem-solving, analytical, and collaboration skills.

Good to Have :

- AWS Certification (e.g., AWS Certified Machine Learning Specialty).

- Experience with deep learning models for NLP, Computer Vision, or Recommendation Systems.

- Familiarity with streaming data solutions (Kafka, Kinesis).

- Exposure to distributed training frameworks (Horovod, Ray).

- Knowledge of security, compliance, and cost-optimization in cloud environments.