Machine Learning Engineer

This is a remote position.

Job Summary:

We are seeking an experienced Machine Learning Engineer to join our dynamic team. The ideal candidate will have 5-8 years of hands-on experience in designing, developing, and deploying machine learning models and AI-driven solutions. You will work closely with data scientists, software engineers, and product teams to build scalable ML solutions that drive business impact.

Key Responsibilities:

• Develop and deploy machine learning models for various applications, including recommendation systems, NLP, and predictive analytics.
  

• Design and implement scalable data pipelines and model training workflows.
  

• Work with large-scale structured and unstructured data, ensuring high-quality data processing and feature engineering.
  

• Optimize and fine-tune ML models for performance, accuracy, and scalability.
  

• Collaborate with cross-functional teams, including data scientists, product managers, and software engineers, to integrate ML models into production systems.
  

• Stay updated with the latest advancements in machine learning, deep learning, and artificial intelligence.
  

• Conduct A/B testing and evaluate model performance using appropriate metrics.
  

• Ensure responsible AI practices, including model explainability, fairness, and security.
  

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Requirements

Required Qualifications:

• 5-8 years of experience in machine learning, deep learning, or AI engineering.
  

• Strong programming skills in Python, Scala, or Java.
  

• Proficiency in machine learning frameworks (TensorFlow, PyTorch, Scikit-learn, etc.).
  

• Experience with cloud platforms (AWS, GCP, or Azure) for deploying ML models.
  

• Expertise in big data technologies (Spark, Hadoop, Kafka) is a plus.
  

• Experience with MLOps practices, including CI/CD pipelines for ML models.
  

• Solid understanding of data structures, algorithms, and software engineering principles.
  

• Strong problem-solving skills and ability to work independently.
  

Preferred Qualifications:

• Experience with natural language processing (NLP), computer vision, or reinforcement learning.
  

• Familiarity with containerization technologies (Docker, Kubernetes) for model deployment.
  

• Experience in handling real-time streaming data and working with time-series forecasting.
  

• Background in statistics, optimization, or mathematical modeling.
  

Education:

• Bachelor's or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field.