Tech Lead Machine Learning/Data Engineer

Encora Inc.; Teletrabalho; BRL 120.000 - 160.000; Tempo integral

Resumo da oferta

Uma empresa de tecnologia em Cariacica está em busca de um(a) Tech Lead Machine Learning/Data Engineer. O(a) candidato(a) ideal terá um bacharelado em áreas como Estatística ou Ciência da Computação, com forte conhecimento de Python e modelagem estatística. Será responsável por trabalhar com uma equipe qualificada para implementar e integrar modelos de Machine Learning, avaliando seu desempenho com dados reais. Vaga oferece a modalidade de trabalho remoto.

Qualificações

• Desejo de combinar teoria e habilidades para resolver problemas utilizando técnicas de Machine Learning.
• Experiência prática em modelagem e avaliação de Machine Learning com Python.
• Desejo de trabalhar com gerentes de produtos e engenheiros de software.

Responsabilidades

• Trabalhar com uma equipe altamente qualificada para implementar modelos de Machine Learning.
• Integrar modelos em serviços através da criação de DAGs e processos ETL.
• Avaliar desempenho do modelo com dados reais e remodelar conforme necessário.

Conhecimentos

Análise estatística

Modelagem e integração de Machine Learning

Trabalho em equipe

Conhecimento em Python

Habilidade em SQL

Conhecimento em modelagem estatística

Formação académica

Bacharelado em Estatística, Ciência da Computação, Matemática Aplicada ou áreas relacionadas

Ferramentas

Python

PySpark

Airflow

AWS

Azure

GCP

Descrição da oferta de emprego

Tech Lead Machine Learning/Data Engineer Encora Inc.•cariacica, estado do espírito santo, Brazil

Descrição da vaga

Tech Lead Machine Learning/Data Engineer

Important Information

Location: Brazil

Job Mode: Full-time

Work Mode: Work from home

Responsibilities and Duties

• Work with a high skilled team to leverage complex and high quality machine learning and statistical models;
• Implement model to service integration via DAG creations and ETL processes;
• Evaluate model performance under real data testing results and remodelate accordingly;
• Build scalable models and DAGs to enable new workflows creations in a high-usage, high-demand environment;
• Work with worldwide multidisciplinary distributed team, participate in technical discussions and definitions using English as main communication language;
• Leverage accurate model architecture and documentation.

Essential Skills

• Bachelor’s degree in Statistics, Computer Science, Applied Mathematics, Electrical Engineering, Physics or related areas;
• Desire to combine theory and abilities to solve problems pragmatically, applying Machine Learning techniques and integrating them into larger systems;
• Desire to work with product managers and software engineers, translating requirements into design and models into end-to-end production code;
• Knowledge in probability and statistical modeling;
• Hands-on experience in statistical analysis and Machine Learning modeling using Python;
• Hands-on experience on model evaluation, integration, data transformation and deployment, covering the complete end-to-end cycle;
• Knowledge in SQL and relational databases;
• Knowledge with DAG definition and implementation.

Highly Desirable Skills

• Experience with Python notebooks, pandas;
• Experience with PySpark, Airflow;
• Experience with cloud tools (AWS, Azure, GCP) and orchestration tools;
• Knowledge about model life cycle, data drift and model drift;
• Experience with data structures;
• Experience with finops data treatment and cost saving analysis.

About Encora

Encora is the preferred digital engineering and modernization partner of some of the world’s leading enterprises and digital native companies. With over 9,000 experts in 47+ offices and innovation labs worldwide, Encora’s technology practices include Product Engineering & Development, Cloud Services, Quality Engineering, DevSecOps, Data & Analytics, Digital Experience, Cybersecurity, and AI & LLM Engineering.

At Encora, we hire professionals based solely on their skills and qualifications, and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality.