ML Engineer
ML Engineer
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Job Description
Job Description:
We are looking for a skilled and driven Machine Learning Engineer with 4 years of experience to design develop and deploy ML solutions across business-critical applications. You ll work alongside data scientists software engineers and product teams to create scalable high-impact machine learning systems in production environments.
Build train and deploy ML models for tasks such as classification regression NLP recommendation or computer vision.
Convert data science prototypes into production-ready applications.
Design and implement ETL/data pipelines to support model training and inference.
Optimize models and pipelines for performance scalability and efficiency.
Collaborate with DevOps/MLOps teams to deploy and monitor models in production.
Continuously evaluate and retrain models based on data and performance feedback.
Maintain thorough documentation of models features and processes.
Required Qualifications:
4 years of hands-on experience in machine learning data science or AI engineering roles.
Proficiency in Python and ML frameworks such as scikit-learn TensorFlow PyTorch or similar.
Solid understanding of ML algorithms data preprocessing model evaluation and tuning.
Experience working with cloud platforms (AWS/GCP) and containerization tools (e.g. Docker).
Familiarity with SQL and NoSQL databases and working with large-scale datasets.
Strong problem-solving skills and a collaborative mindset.
Good to Have:
Experience with MLOps tools (e.g. MLflow SageMaker Kubeflow).
Knowledge of deep learning transformers or LLMs.
Familiarity with streaming data (Kafka Spark Streaming) and real-time inference.
Exposure to ElasticSearch for data indexing or log analytics.
Interest in applied AI/ML innovation within domains like fin-tech healthcare or ecommerce.
Education:Bachelor s or Master s degree in Computer Science Data Science AI/ML or a related field.
Bachelor s degree in Computer Science, Information Technology, or related field. Proven experience in production security, DevSecOps, and SDLC practices. Strong knowledge of security tools such as Qualys, Black Duck, and JFrog Xray. Experience in incident response management and security incident handling. Excellent problem-solving skills and ability to work under pressure. Effective communication skills and ability to collaborate with cross-functional teams. Relevant certifications (e.g., CISSP, CEH) preferred.
Employment Type
Full Time
