Remote Senior Engineer – AI Data Generation & Optimization Research

Description:

• Axelera is a European, high-growth Series B startup focused on revolutionizing the AI landscape with an in-memory computing platform.
• The company specializes in creating AI hardware and software optimized for high-performance inference, targeting high-end edge computing, embodied AI, and server-side AI deployments.
• The role is for an AI Research Engineer with a strong focus on data generation, selection, and optimization.
• The engineer will advance the platform’s capabilities for generating high-quality datasets, selecting the right data for training AI models, and optimizing data pipelines for performance and scalability.
• The position involves creating sustainable data processes that enable continuous improvement in AI models, contributing to a competitive edge for the products.
• Responsibilities include developing innovative techniques for synthetic data generation, designing data selection strategies, building a self-sustaining data generation and selection loop, collaborating with cross-functional teams, staying updated with the latest research, and implementing best practices for model testing and deployment.

Requirements:

• Proven experience in developing and optimizing data pipelines for machine learning, focusing on data generation, augmentation, or selection techniques.
• Strong technical skills in data-centric AI approaches, including data cleaning, augmentation, and synthetic data generation.
• Proficiency in programming languages like Python, and experience with data manipulation libraries (e.g., NumPy, Pandas) and nearest neighbour search libraries (e.g., FAISS).
• Familiarity with machine learning frameworks such as TensorFlow, PyTorch, or JAX.
• Knowledge of optimization techniques for large-scale data pipelines, data storage, and distributed computing.
• A strong understanding of the latest advancements in AI/ML research, particularly in data optimization, with strong analytical skills to enhance data quality and model performance.
• Ability to work in a collaborative, fast-paced startup environment and communicate complex technical concepts clearly.
• Preferred qualifications include a PhD or advanced degree in Computer Science, Machine Learning, AI, or related fields, 5+ years of relevant work experience, experience with large-scale data systems, familiarity with reinforcement learning or generative modeling techniques, and a passion for data-driven AI development.

Benefits:

• The opportunity to play a key role in shaping the future of AI by developing foundational data systems that drive innovation and optimize AI models at scale.
• A highly collaborative, fast-growing team culture that values innovation, continuous learning, and tackling challenging real-world problems.
• Significant opportunities for personal and professional growth, with a chance to influence product direction and technology strategy as a Series B startup.
• Competitive salary, equity options, and a comprehensive benefits package.