Senior Machine Learning Engineer

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OpenTeams

WebsiteLinkedInAll Job Openings

11 - 50 employees

💼 Consulting

📣 Marketing

☁️ SaaS

💰 $100k Pre Seed Round on 2019-08

Consulting • Marketing • SaaS

OpenTeams is a company that provides a comprehensive platform and marketplace for enterprises to access, implement, and support open source solutions. By bridging the gap between open source communities and businesses, OpenTeams offers commercial support, training, and services necessary to optimize the use of open source technologies. They help organizations overcome challenges related to open source adoption, including security, compatibility, and customization, and provide support in recruiting open source talent. OpenTeams also offers business process outsourcing services for software consultancies, covering areas like HR, marketing, and accounting. With a strong emphasis on community engagement and collaboration, OpenTeams facilitates business innovation through trusted open source partnerships.

📋 Description

• Develop and refine features for deep learning models using large-scale customer and behavioral datasets • Implement model architecture changes informed by recent academic research • Collaborate with client teams to understand business context and translate requirements into technical solutions • Optimize model training pipelines for efficiency and scalability • Document approaches, findings, and technical decisions for knowledge sharing • Participate in code reviews and contribute to engineering best practices • Support a strategic client engagement focused on deep learning model development for customer behavior prediction • Enhance and optimize deep-learning models that drive business decisions at scale • Contribute to production systems and apply cutting-edge academic research techniques

🎯 Requirements

• Strong proficiency with a deep learning framework, such as PyTorch or TensorFlow • Hands-on experience with feature engineering for predictive models • Solid foundation in machine learning fundamentals, including supervised learning, neural network architectures, and optimization • Ability to read, understand, and implement techniques from ML research papers • Python proficiency in a data science/ML context • Comfortable working in ambiguous environments and adapting to unfamiliar tooling • Authorized to work where they live • Western Hemisphere timezone required • U.S. strongly preferred • Nice to have: experience with time-series or sequential modeling • Nice to have: MLOps experience, including model deployment, monitoring, and pipeline orchestration • Nice to have: familiarity with Google Cloud Platform or large-scale distributed training • Nice to have: background in causal inference or attribution modeling • Nice to have: experience working in consulting or a client-facing technical role

🏖️ Benefits

• 100% employer paid medical premiums for employees • Self-managed PTO with a minimum time off requirement • Career framework providing a pathway and recognition of increased impact • Opportunities to collaborate with global experts • Opportunities to contribute to open source projects • Support to learn fast • Recognition for successful collaboration