Posted:3 weeks ago|
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Full Time
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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.
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.
Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, or a related field.
SquareShift Technologies
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