Ml/Ai Developer Jobs

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We are seeking a highly skilled and motivated Machine Learning Engineer to join our talented team. As a Machine Learning Engineer at Predactica, you will play a crucial role in designing, developing, and deploying advanced machine learning models and algorithms to create transformative solutions for our clients.

Responsibilities

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Collaborate with cross-functional teams to understand business requirements and identify opportunities to leverage machine learning techniques effectively.

Create and deploy ML models using Deep learning techniques

Conduct data analysis and preprocessing to prepare datasets for model training and evaluation.

Design, implement, and fine-tune machine learning models for various applications, such as natural language processing, computer vision, recommendation systems, and predictive analytics.

Utilize state-of-the-art tools and frameworks for model development and deployment, ensuring scalability and performance.

Evaluate model performance and continuously optimize models to achieve the best results.

Integrate machine learning models into production systems and monitor their performance in real-world applications.

Stay up-to-date with the latest advancements in machine learning and contribute to research and innovation within the field.

Requirements

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Bachelor's degree or higher in Computer Science, Engineering, Mathematics, or a related field.

3+ years of hands-on experience in developing and deploying machine learning models in real-world applications.

Background in Statistics

Proficiency in programming languages such as Python, R, or similar, and familiarity with relevant libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn).

Strong understanding of various machine learning techniques, including supervised and unsupervised learning, deep learning, and reinforcement learning.

Experience with data preprocessing, feature engineering, and data visualization.

Knowledge of cloud platforms (e.g., AWS, Azure, GCP) and experience with deploying ML models in cloud environments.

Solid understanding of software development practices, version control systems, and agile methodologies.

Excellent problem-solving and analytical skills, with the ability to translate business requirements into technical solutions.

Strong communication and teamwork skills, with the ability to collaborate effectively with cross-functional teams.

Preferred

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Masters or PhD in Computer Science with statistics background

Experience with Explainable AI (XAI) techniques and a focus on model interpretability.

Contributions to open-source machine learning projects or publications in relevant conferences/journals.

Experience in deploying machine learning models in production systems at scale.