
1001 - 5000 employees
Founded 2002
đź Gaming
đĄ Telecommunications
Software Development âą Gaming âą Telecommunications
Sigma Software Group is a multinational company, established in 2002, that specializes in providing high-quality software development, graphic design, testing, and support services. The company focuses on delivering solutions across various industries such as automotive, telecommunications, aviation, advertising, gaming, banking, real estate, and healthcare. Sigma Software values professional growth, offers remote work opportunities worldwide, and caters to world-renowned clients like AstraZeneca, Scania, and SAS. The company emphasizes a culture of continuous education, mentorship, and flexible work environments, making it a preferred workplace for IT specialists aiming to work on complex solutions utilizing cutting-edge technologies. Sigma Software is committed to innovative solutions and engineering the future while also contributing to social causes such as charitable work in Ukraine.
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1001 - 5000 employees
Founded 2002
đź Gaming
đĄ Telecommunications
Software Development âą Gaming âą Telecommunications
Sigma Software Group is a multinational company, established in 2002, that specializes in providing high-quality software development, graphic design, testing, and support services. The company focuses on delivering solutions across various industries such as automotive, telecommunications, aviation, advertising, gaming, banking, real estate, and healthcare. Sigma Software values professional growth, offers remote work opportunities worldwide, and caters to world-renowned clients like AstraZeneca, Scania, and SAS. The company emphasizes a culture of continuous education, mentorship, and flexible work environments, making it a preferred workplace for IT specialists aiming to work on complex solutions utilizing cutting-edge technologies. Sigma Software is committed to innovative solutions and engineering the future while also contributing to social causes such as charitable work in Ukraine.
âą Design, develop, and optimize scalable Machine Learning models for advertising intelligence and forecasting systems âą Analyze large-scale historical and real-time datasets to improve forecasting accuracy and monetization strategies âą Build and maintain distributed data processing pipelines using Spark and related Big Data technologies âą Develop production-ready ML solutions using Python within AWS cloud infrastructure âą Research, evaluate, and implement Machine Learning algorithms suitable for high-load AdTech environments âą Improve model performance, scalability, reliability, and operational efficiency âą Collaborate with Data Engineers, Product Managers, and distributed engineering teams to deliver end-to-end ML solutions âą Contribute to ML architecture decisions, experimentation approaches, and engineering best practices âą Monitor, validate, and optimize ML model quality and forecasting performance in production environments âą Produce technical documentation related to ML pipelines, models, and distributed systems âą Mentor engineers and support technical growth within the team âą Drive innovation in Machine Learning and AdTech technologies
âą 6+ years of commercial experience in Machine Learning and Big Data engineering âą Strong hands-on experience with machine learning algorithms implementation using Python âą Proven experience with Apache Spark and large-scale distributed data processing âą Experience working with distributed messaging systems such as Kafka âą Strong knowledge of AWS cloud services and cloud-native architectures âą Experience designing and developing large-scale distributed or mission-critical systems âą Solid understanding of software engineering principles, SDLC, and Agile methodologies âą Strong analytical thinking and problem-solving skills âą Ability to work independently and take ownership of complex technical solutions âą Good communication and collaboration skills âą Upper-Intermediate or higher English level âą WILL BE A PLUS: Experience with Golang âą Experience in AdTech, online advertising, or media platforms âą Experience with forecasting systems or recommendation engines âą Experience optimizing ML models for large-scale production environments
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