Machine Learning Engineer
Who We Are
In 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 global company, with offices across the globe, we continue to partner with the world's leading brands, such as 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 Flexibility
This 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 Opportunity
As 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 development;
Bachelor 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 integrating the models with the tools in Hadoop or others);
Software development experience from scoping, requirements design, development, integration, testing, go live to PROD (vs internal research work);
Ability to work on distributed cloud platforms;
Fluent English.
Why Poatek?
In addition to being part of an international and innovative consultancy company, you will have:
Flexible hours and autonomy;
Work with cutting-edge technologies;
Partner with global and relevant brands in the market;
Collaborative team and learning ecosystem;
Career development plan & growth;
International travel opportunities (optional).
Some of our benefits:
Health and dental plan
Life insurance
Monthly voucher for meals, culture, education, health and mobility
Child 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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