Deep Learning Researcher

Company Description
noira.dev is an all-in-one digital partner focused on delivering modern, scalable technology solutions for a wide range of clients. The company brings together expertise in software development, data, and design to help organizations build and grow digital products. As a remote-first organization, noira.dev values autonomy, clear communication, and a collaborative mindset. Team members are encouraged to explore innovative technologies and approaches to solve complex business and technical challenges. Joining noira.dev offers the opportunity to contribute to impactful digital initiatives while working with a multidisciplinary international team.
Role Description
This is a full-time remote role for a Deep Learning Researcher at noira.dev. In this role, you will design, implement, and evaluate deep learning models for real-world applications, collaborating closely with engineering and product teams to integrate your work into production systems. You will conduct literature reviews, experiment with state-of-the-art architectures, and optimize models for performance, robustness, and scalability. Daily responsibilities include building and maintaining datasets, writing clean and reproducible research code, documenting findings, and presenting results to technical and non-technical stakeholders. You will also help define research directions, contribute to internal tools and frameworks, and support continuous improvement of the company’s AI capabilities.
Qualifications
Strong foundation in machine learning and deep learning, including neural network architectures, optimization methods, and model evaluation.
Proficiency in Python and common deep learning frameworks (e.g., PyTorch, TensorFlow, JAX) for building and training models.
Experience with data processing and analysis tools (e.g., NumPy, pandas, SQL) and working with large or complex datasets.
Background in applied mathematics, statistics, or computer science, with solid understanding of linear algebra, probability, and numerical methods.
Ability to design experiments, run systematic benchmarks, and clearly interpret and communicate results.
Familiarity with software engineering best practices, including version control (Git), testing, and reproducible workflows.
Comfort working in a remote, collaborative environment, with clear written and verbal communication skills.
Master’s or PhD in Computer Science, Machine Learning, or a related field is preferred; relevant industry or research experience is highly valued.
Experience deploying models to production, working with cloud platforms, or optimizing models for latency and resource usage is a plus.
Interest in staying current with deep learning research and contributing ideas that can translate into practical solutions for clients.

Work arrangement
Yes