Cymetrix Software

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. (ref:hirist.tech)