Are you a Machine Learning Enthusiast with desire to develop high-end intelligent products? Do you want to work on exciting algorithmic and deep learning challenges? Are you seeking an environment that drives innovation? Are you looking for a company with large amounts of data?
Well, then this role was made for you! Get ready to join the largest Online Travel Agency in South Eastern Europe, with a footprint that covers more than 45 countries, become member of the awesome Product Development team and work in our fantastic offices in the heart of Athens!
As a Machine Learning Engineer, you will be engaged to solve complex business problems which a machine is better capable to answer than a human being. You will be at the center of defining how we build and deploy systems around intelligent algorithms. You will play a key role in analyzing and understanding large amount of business data for evaluation, innovation and prediction. You will use statistical and machine learning techniques to develop algorithms and improve existing systems and applications.
- Design & develop machine learning algorithms and write code to run experiments and derive solutions to address critical problems such as credit card fraud detection for example.
- Prototype machine learning models by using high-level modeling languages such as R or Python.
- Discover, design, and develop analytical methods to support novel approaches of data and information processing.
- Implement clean APIs and frameworks to be generalized to a number of business problems, in multiple languages and platforms.
- Continuously measure effectiveness of machine learning algorithms and optimize solutions for performance and scalability.
- Analyze and extract relevant information from large amounts of tripsta’s business data to improve our existing systems and our user's experience.
- Ensure a good data flow.
- Work closely with software engineering teams to drive new feature creation and other functional teams to create and improve algorithms and processes.
- Collaborate with our dedicated data analysis team to establish scalable, efficient, automated processes for large-scale data analyses, model development, model validation and model implementation.
- Interact with business teams to develop an understanding of their business requirements and operational processes.
Qualifications and key competencies
- Bachelor Degree in Computer Science, Applied Mathematics, Statistics, Electrical Engineering or a highly quantitative field.
- Master's/PhD in Machine Learning or a related field would be considered a plus.
- Minimum 3-4 years hands-on experience developing and implementing Machine Learning algorithms and models.
- Proven track record of innovating in Machine Learning algorithms and applications.
- Excellent command of English, both written and oral.
- Solid communication and data presentation skills.
- Problem solving ability.
- Ability to efficiently plan, prioritize and manage numerous projects and tasks simultaneously.
- Highly quantitative thinking, strong Mathematical and analytical skills.
- Detail orientation.
- Discipline, diligence & accountability.
- Desire for continuous learning and skills improvement.
- Fulfilled military obligations.
Required Skills and Knowledge
- Programming and prototyping skills (Java/C++ and R/MATLAB/Python), sufficient to extract, transform, and clean large data sets in a Unix/Linux environment.
- Big data, and big data toolset experience.
- Deep understanding of current applied machine learning techniques.
- Experience designing and supporting large-scale distributed systems in a production environment.
- Comfortable conducting design and code reviews.
- Passionate about working with large unstructured and structured data sets.
- Experience in collaborating across multiple teams including data analysis, business intelligence, and software engineering.
- Understanding the entire lifecycle of machine learning product development, from inception to production.
- Independent and able work well in green-field development environments.
- Excited about building things and experimenting.
- Ability to convey rigorous mathematical concepts and considerations to non-experts.
- Ability to distill problem definitions, models, and constraints from informal business requirements; and to deal with ambiguity and competing objectives.
- Ability to own projects end-to-end.
- Experience in solving large scale relevance problems and comfortable doing incremental quality work while building brand new systems to enable future quality improvements.
- Experience in changing, high-growth environments.