ATPCO is seeking a Senior Machine Learning Engineer to join our team dedicated to tackling some of the most exciting and impactful data challenges within the airline industry. This role offers an opportunity to develop innovative Artificial Intelligence (AI), Machine Learning (ML), and Data Science solutions for rapidly evolving airline industry, harnessing hundreds of terabytes of data daily, and leveraging the latest AWS technologies to drive innovation at scale.

As a Senior Machine Learning Engineer, you are proficient in developing and implementing AI and machine learning models and algorithms to solve diverse challenges and opportunities. You will work with cross-functional teams, including data scientists, data engineers, and business stakeholders to deliver end-to-end AI and Machine Learning solutions. You will also perform comprehensive data management including preprocessing, feature engineering, and model evaluation to improve accuracy and efficiency.

Responsibilities:

The role of a Senior Machine Learning Engineer intersects with various fields, including Data Engineering, Software Engineering, Data Science and AI/ML Modeling. In this position, you will be responsible for carrying out a range of machine learning engineering tasks, which include one or more of the following:

Prototype and iterate on AI/ML solutions, embracing a curious and experimental approach to problem-solving. Stay curious and be a continuous learner with new AI/ML advancements, applying them to foster innovation.
Collaborate with data scientists, analysts, and other stakeholders to understand complex business and analytic problems using data science principles and established tools
Work on multi-project assignments with multiple business units and across multiple data platforms
Design, build, test, validate, and deploy AI and Machine Learning models that solve real-world business problems.
Develop end-to-end AI/ML based solutions that optimize business workflows, processes and user experiences
Retrain, maintain, and monitor models in production.
Easily communicate your modeling solution decisions using your understanding of AI/ML techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation.
Leverage CI/CD best practices, including test automation and monitoring, to ensure successful deployment of AI/ML models and application code.
Mentor, develop and train other junior AI/ML practitioners

Qualifications:

Bachelor’s or master’s degree in computer science, Statistics, Mathematics, Engineering or a related field.
Proven experience as a machine learning engineer, with at least 5 years of experience in developing and deploying large scale AI/ML models and/or systems in production environment, including batch and/or real-time data processing, model containerization, CI/CD pipelines, API development, model training and productionizing ML models
Experience with LLMs and advanced Generative AI tools and frameworks.
Strong fluency in languages like Python and SQL, with proficiency in one or more industry recognized ML frame works (e.g., scikit-learn, PyTorch, TensorFlow, Keras).
In-depth knowledge of SQL and experience working with relational and non-relational databases (e.g., MySQL, PostgreSQL, MongoDB, Cassandra)
Experience with managing large scale data processing using big data cloud services. Experience with AWS services like Redshift, AWS Glue, AWS EMR, and AWS S3 is a plus.
Strong understanding of data modeling concepts and data management principles.
Strong understanding of real-time data streaming architectures using AWS services like Amazon Kinesis or Apache Kafka.
Knowledge of Data Mesh principles and understanding of designing and implementing data architectures following Data Mesh concepts within the AWS ecosystem.
Familiarity with AWS security services and features for data security and privacy.
Strong problem-solving and troubleshooting skills, with the ability to identify and resolve complex data engineering issues.
Excellent communication and collaboration skills, with the ability to work effectively with technical and non-technical stakeholders.
Relevant AWS certifications (e.g., AWS ML Specialty, AWS AI Practitioner) would be a plus.
Airline and travel industry experience would be a plus.