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Job Information
Dogma Alares Machine Learning Engineer in Istanbul, Turkey
Company overview
Dogma Alares is the next generation consulting house founded on four multi-disciplinary capabilities natively blended in nature for an exponentially changing and complex world. Our capability areas are:
Strategy consulting
Machine learning
Experience & service design
Innovation & new digital technologies
We provide professional services and advise to leading institutions across different industries with particular focus on financial services and consumer goods / services.
Role overview
As Dogma Alares, we acknowledge Machine Learning and AI as one of our four pillars and we position machine learning engineers at the core of our project squads. We are looking for candidates who have a firm grasp of machine learning algorithms, data analytics, software development practices and eager to transfer into the field by contributing on projects for various industries solving different problem sets.
We want to welcome new members of our team, where they will have the opportunity to apply their existing theoretical and practical knowledge onto real-life cases while boosting their understanding of engineering and business. We offer a nourishing, empowering and interdisciplinary environment with a wide range of collective sectoral experience through seniors and experts of various fields, and client-side working experience.
Main responsibilities of the role
Working closely with ML Engineers, Software Developers, Management Consultants and Service Designers to set business problems and produce executable solutions
Working with the experts to set the standards for industry-grade machine learning and software engineering practices
Helping to define and develop successful, robust and scalable models at every phase, including:
Deciding convenient approaches and suitable tools
Gathering, transforming and processing data
Applying statistical analysis and prescription
Building, testing and deploying models
Reverse engineering or refactoring existing solutions to better understand, improve and extend their impacts and benefits
Following both academic and industrial developments regarding AI/ML applications; publishing relevant content if possible
Qualifications for the role
MSc/PhD or degree in Computer Science or a relevant subject. Surprise us with your skills without these degrees!
Excellent command of spoken and written English
Well-established foundation of machine learning principles and software engineering standards
Solid understanding of statistical and machine learning algorithms and models, such as tree-based methods, probabilistic approaches, linear/nonlinear models, and deep learning
Knowledge and experience of computer vision, natural language processing, signal processing and big data practices
Good coding skills, especially in Python. Experience with standard libraries in ML pipelines such as NumPy, SciPy, Pandas, PySpark, SciKit-Learn, TensorFlow/PyTorch, NLTK, GenSim, OpenCV, MatPlotLib, Seaborn, etc.
Familiarity with relational/non-relational databases, application development frameworks, and POSIX-based systems
What we offer
Fast-paced and objective career growth
Empowering working environment
Start-up setup in a professional working culture
Exposure to collective industry experience
Joining a talented and passionate team and network of senior experts
Working closely with a large partner team
20 days holiday per year
Learning and development budget
Support for flexible working models
Great company culture
More About Us
This is Dogma Alares. A next generation consulting firm. Our motto is challenging the dogmas. This requires multiple skills in a flourishing culture as we bring together multidisciplinary teams including strategy consultants, machine learning experts, software developers and designers when we provide services to clients across different industries.
Partner Team: https://www.dogmaalares.com/team
Company Culture: https://www.dogmaalares.com/career-cultural-principles
Culture Code: https://www.dogmaalares.com/career
Please note that only short-listed candidates will be contacted.