Machine Learning Engineer

About the position

As a Machine Learning Engineer, you will be responsible for developing and implementing cutting-edge machine learning algorithms and models to improve our aerospace products and services. You will work closely with a team of engineers and data scientists to analyze large datasets, identify patterns and trends, and develop predictive models to enhance our products and services. Key Responsibilities: - Develop and implement machine learning algorithms and models to improve our aerospace products and services - Work closely with a team of engineers and data scientists to analyze large datasets and identify patterns and trends - Collaborate with cross-functional teams to understand business needs and translate them into technical requirements - Design, build, and deploy scalable machine learning solutions - Monitor and maintain the performance of machine learning models and make necessary adjustments - Stay up-to-date with the latest advancements in machine learning and incorporate them into our products and services - Communicate complex technical concepts to non-technical stakeholders - Participate in code reviews and provide constructive feedback to improve the overall quality of the codebase - Contribute to the development of best practices and standards for machine learning at Premieraerospace Requirements: - Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field - 2+ years of experience in machine learning, data science, or a related field - Strong programming skills in languages such as Python, R, or Java - Experience with machine learning libraries and frameworks such as TensorFlow, Keras, or PyTorch - Proficiency in data manipulation and analysis using SQL and other tools - Knowledge of data visualization techniques and tools - Experience with cloud computing platforms such as AWS, Azure, or Google Cloud - Excellent problem-solving and analytical skills - Strong communication and teamwork abilities - Ability to work independently and manage multiple projects simultaneously

Place of work