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Machine Learning Engineering Manager
ГибридПолная занятостьEngineering ManagementTravel and Tourism
Lead and develop a team of machine learning and data engineers building scalable data pipelines, ML infrastructure, and ranking and recommendation solutions. Shape the technical roadmap, guide architecture decisions, support production deployment, and mentor team members in a hybrid role based in or
Обязанности
- Lead and develop a high-performing team of machine learning and data engineers
- Define and execute the team’s ML and platform roadmap
- Build scalable ML infrastructure, data pipelines, and evaluation systems
- Guide architecture decisions based on cost, business needs, and emerging technologies
- Enable production deployment and model inference in collaboration with software engineers
- Monitor application health, metrics, model performance, and maintenance needs
- Translate stakeholder and business requirements into viable ML solutions
- Evaluate and integrate new machine learning technologies and tooling
- Drive model retraining, optimization, scaling, and continuous improvement
- Make technical decisions and ensure reliable delivery across the team
- Mentor, coach, and support the professional development of team members
- Contribute to machine learning training, exploration, and technical knowledge sharing
Требования
- At least 3 years of experience leading an ML engineering team of at least four people in a production environment
- Master’s degree, PhD, or equivalent experience in a quantitative field such as computer science, engineering, mathematics, artificial intelligence, or physics
- Relevant experience applying machine learning to business problems
- Strong knowledge of recommender systems, deep learning, information retrieval, causal inference, or ML model scaling
- Experience designing and deploying end-to-end machine learning solutions
- Experience with cloud ML frameworks such as AWS SageMaker and tools including TensorFlow, PyTorch, or scikit-learn
- Experience with big-data frameworks such as PySpark, Apache Flink, Snowflake, or similar technologies
- Experience with relational or NoSQL databases such as MySQL, Cassandra, or DynamoDB
- Strong understanding of machine learning algorithms, statistical models, and data structures
- Working knowledge of Python, Java, Kafka, Hadoop, SQL, Spark, and version control systems
- Experience collaborating with engineering, UX, and product stakeholders
- Excellent written and spoken English
Условия и преимущества
- Competitive compensation and benefits package
- Annual paid time off and generous parental, grandparent, bereavement, and care leave
- Hybrid working with flexible arrangements
- Up to 29 days per year working from abroad within the home country
- Product discounts, Genius Level 3 status, and wallet credit