Machine Learning Engineer

Job Title: Machine Learning Engineer

Company: Digital Solutions Tech
Location: Remote
Employment Type: Full-time

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🧠 Job Description:

We are looking for a Machine Learning Engineer to help us design, develop, and deploy innovative ML models and intelligent systems. You will work closely with data scientists, software engineers, and product teams to turn data-driven insights into scalable and robust solutions.

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💼 Key Responsibilities:

Design and implement machine learning algorithms and models for prediction, classification, recommendation, and more.

Preprocess, clean, and transform large datasets for model training and evaluation.

Train, validate, and tune ML models to optimize performance.

Deploy ML models into production environments using MLOps practices.

Collaborate with software engineers to integrate ML models into existing systems or applications.

Monitor model performance and retrain/update as necessary.

Document experiments, code, and project outcomes for reproducibility and transparency.

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✅ Basic Qualifications:

Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, or related field.

Proficiency in Python and ML libraries like Scikit-learn, TensorFlow, PyTorch, or Keras.

Solid understanding of statistics, probability, and linear algebra.

Experience with data processing tools (Pandas, NumPy) and visualization (Matplotlib, Seaborn).

Familiarity with cloud platforms (AWS, GCP, Azure) and version control (Git).

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⭐ Preferred Qualifications:

Experience with deep learning frameworks and NLP techniques.

Exposure to MLOps tools (MLflow, Airflow, Docker, Kubernetes).

Knowledge of big data technologies (Spark, Hadoop) is a plus.

Hands-on experience with model deployment and API integration.

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🎯 Key Skills:

Python, TensorFlow, PyTorch, Scikit-learn, Data Preprocessing, Model Deployment, Cloud Computing, MLOps, Machine Learning, Deep Learning, NLP

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📈 Why Join Us?

Work on cutting-edge AI projects with real-world impact.

Collaborative and innovative team environment.

Growth and learning opportunities in the AI/ML space.