Descrição da Vaga
Machine Learning EngineerWho We AreIn 2021, Poatek was acquired by WillowTree, an award-winning digital product consultancy recognized as one of the fastest growing and best places to work in the United States.
Now a , with offices across the globe, we continue to partner with the world’s leading brands, such as the FOX, Capital One, HBO, PepsiCo, Domino’s and more, to design, build, and transform their digital products and strategies.
We’re looking to grow our Poatek offices in Brazil with top talent excited to collaborate with team members across the globe to deliver innovative solutions for our clients.
Location and FlexibilityThis is a hybrid role.
This model requires the ability to work in a hybrid mode from one of our offices in São Paulo (2 times/ week or 8 days/ month) or Porto Alegre (3 times/ week or 12 days/ month).
Our WFN culture is designed to foster in-person innovation, collaboration, and connection with team members local and visiting from other global offices.
The OpportunityAs a Machine Learning Engineer on our team, you'll design, develop, and deliver machine learning solutions, decipher loosely defined problems using complex datasets, and determine appropriate analytical and modeling techniques.
You'll analyze structured and unstructured data, establish automated processes for large-scale modeling, perform exploratory analysis, and collaborate with peers on data acquisition and exploration, demonstrating a strong sense of ownership and urgency.
Responsibilities Work on all aspects of the design, development and delivery of machine learning enabled solutions for our clients;
Come up with solutions to loosely defined business problems by leveraging pattern detection over complex datasets across multiple platforms;
Establish efficient, automated processes for large-scale modeling;
Become part of a highly skilled and geographically distributed team;
Collaborate with peers on problem definitions, data acquisition, data exploration, visualization as well as building the tools that support this process;
Strong sense of ownership, urgency and drive.
Qualifications Relevant experience in data science/ machine learning developmentBachelor and/or Master degree in Statistics, Mathematics, Physics, Computer Science or other related subject.
Proficiency in Python.
Experience with machine learning frameworks (like Keras, TensorFlow, or PyTorch) and libraries (like scikit-learn).
Strong understanding of machine learning algorithms, processes, tools and platforms.
Experience with container management and machine learning deployment frameworks, such as Kubernetes, Kubeflow and MLFlow.
Big Data Hadoop work experience (either integration the models with the tools in Hadoop or other)Software development experience from scoping, requirements design, development, integration, testing, go live to PROD (vs internal research work)Ability to work on distributed cloud platformsFluent English Why Poatek?In addition to being part of an international and innovative consultancy company, you will have: Flexible hours and autonomyWork with cutting edge technologiesPartner with global and relevant brands in the marketCollaborative team and learning ecosystemCareer development plan & growthInternacional travel opportunities (optional) Some of our benefits: Health and dental planLife insuranceMonthly voucher for meals, culture, education, health and mobilityChild care assistance and more! Equality is a principle here at Poatek.
We are committed to building an inclusive team that represents a variety of backgrounds, perspectives, beliefs, and experiences.
Therefore we provide equal employment opportunities to all employees and applicants regardless of race, color, religion, gender identity, sexual orientation, national origin, age, or disability.
We will only use the information you provide to process your application and to produce tracking statistics.
Since we do not request personal data deemed sensitive, we ask you to abstain from sharing those information with us.
For more information on how we use your information, see our Privacy Policy.
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