Senior Machine Learning Engineer - Recommendation Systems

What role will you play in the team

As a Senior Machine Learning Engineer, you will lead the development and deployment of advanced recommendation systems, enhancing user engagement and driving business growth. You will contribute to the architecture, design, and implementation of large-scale machine learning pipelines.

What you will do

You will be responsible for designing, building, and maintaining machine learning models for personalized recommendations. You will collaborate with data engineers, product managers, and other stakeholders to understand business requirements and deliver impactful solutions. You will also mentor junior team members and contribute to the improvement of team processes.

Key responsibility

• Design and implement machine learning models for personalized recommendations, including collaborative filtering, content-based filtering, and hybrid approaches.
• Develop and maintain large-scale machine learning pipelines for training, evaluating, and deploying recommendation models.
• Collaborate with data engineers to optimize data pipelines for machine learning.
• Work with product managers to understand business requirements and translate them into technical solutions.
• 
  Evaluate and fine-tune model performance using appropriate metrics and techniques.
• Mentor junior team members and provide technical guidance.
• Stay up-to-date with the latest advancements in machine learning and recommendation systems.
• Conduct A/B tests to evaluate the effectiveness of different recommendation strategies.

Required Qualification and Skills

• Bachelor's or Master's degree in Computer Science, Machine Learning, or a related field.
• 3+ years of experience in building and deploying machine learning models for recommendation systems.
• Proficiency in Python and relevant libraries such as TensorFlow, PyTorch, and scikit-learn.
• Experience with large-scale data processing technologies such as Spark and Hadoop.
• Strong understanding of recommendation system algorithms and techniques.
• Excellent communication and collaboration skills.

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• Experience with cloud computing platforms such as AWS or Azure is a plus.

Benefits Included

• Competitive salary and benefits package, including health insurance, paid time off, and retirement plan.
• Opportunity to work on cutting-edge technology and impactful projects.
• Professional development opportunities, including training, conferences, and tuition reimbursement.
• Flexible work arrangements and a supportive work environment.
• Collaborative and inclusive culture that values diversity and innovation.

A Day in the Life

You will spend your day coding, designing models, collaborating with team members, and analyzing data to improve the performance of recommendation systems. You will also attend meetings and present your work to stakeholders.