Machine Learning Engineer - Apply via TalentIQ.one

The position of Machine Learning Engineer involves developing and implementing machine learning models to solve complex business problems. This role requires collaboration with data scientists and software engineers to build scalable and reliable machine learning systems. The ideal candidate will work on projects involving predictive analytics, natural language processing, and other AI-driven solutions, ensuring models are optimized and deployed effectively into production.

Key Responsibilities:

• Design and build machine learning models and algorithms tailored to business needs.
• Preprocess and analyze large datasets to train, test, and validate models.
• Deploy machine learning models into production and ensure they perform at scale.
• Collaborate with cross-functional teams, including data scientists and engineers, to integrate machine learning solutions into applications.
• Continuously monitor model performance and optimize for efficiency and accuracy.
• Research and implement state-of-the-art techniques in machine learning and AI.
• Automate processes for data collection, cleaning, and feature engineering.
• Document experiments, workflows, and results for clear communication within the team.
• Ensure that all machine learning systems comply with data privacy and security standards.

Skills and Qualifications:

• Expertise in machine learning algorithms and frameworks like TensorFlow, PyTorch, or Scikit-learn.
• Proficiency in programming languages such as Python, R, or Java.
• Strong experience in working with large datasets and data preprocessing.
• Familiarity with cloud services like AWS, Google Cloud, or Azure for deploying machine learning models.
• Excellent problem-solving and analytical skills with a strong mathematical foundation.
• Knowledge of deep learning, reinforcement learning, and NLP is a plus.
• Ability to collaborate and communicate with multidisciplinary teams.
• Experience with big data processing tools such as Hadoop and Spark is an advantage.

Education and Experience:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or related fields.
• 2+ years of hands-on experience in machine learning development and deployment.
• Experience in a software engineering environment is an added benefit.