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AI Research Engineer – Data Generation & Optimization (all seniority levels)

Remote: 
Full Remote
Experience: 
Senior (5-10 years)
Work from: 

Offer summary

Qualifications:

Experience in developing data pipelines, Strong programming skills in Python, Knowledge of AI/ML research advancements, PhD or advanced degree preferred.

Key responsabilities:

  • Develop innovative techniques for synthetic data generation
  • Design and implement data selection strategies

Axelera AI logo
Axelera AI Scaleup https://axelera.ai/
51 - 200 Employees
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Job description

Company Overview
Axelera is a European, high-growth Series B startup revolutionizing the AI landscape with our in-memory computing platform. We specialize in creating AI hardware and software optimized for high-performance inference, catering to cutting-edge use cases across high-end edge computing, embodied AI, and server-side AI deployments. We are looking for passionate, innovative research engineers to join our team and help drive the future of AI.

 

Role Overview
We are seeking an AI Research Engineer with a strong focus on data generation, selection, and optimization. The role will be central to advancing our platform’s capabilities for generating high-quality datasets, selecting the right data for training cutting-edge AI models, and optimizing data pipelines to maximize the performance and scalability of our AI solutions.

You will work closely with our AI researchers and engineers to create sustainable data processes that enable continuous improvement in our AI models, ensuring that our systems become smarter and more efficient over time. Your work will directly contribute to building a competitive edge for our products by harnessing the power of data.

 

Responsibilities:

  • Data Generation: Develop innovative techniques for generating synthetic data or augmenting existing datasets to improve the quality, diversity, and representativeness of training data.

  • Data Selection & Optimization: Design and implement data selection strategies that optimize model performance by choosing the most relevant data for training and validation. Focus on balancing the quality, diversity, and quantity of data to create more accurate models.

  • Data Flywheel Platform: Build and optimize systems that create a self-sustaining data generation and selection loop, allowing the company to continuously collect, process, and refine data for better AI model performance.

  • Collaboration: Work closely with cross-functional teams, including AI researchers, hardware engineers, and software engineers to integrate AI models into the broader platform.

  • Innovation: Stay up-to-date with the latest research in multimodal AI, proposing and implementing new techniques to push the boundaries of what's possible in generative AI.

  • Deployment & Testing: Implement best practices for model testing, deployment, and continuous improvement to ensure models scale effectively in production environments.

 

Requirements:

  • Experience: Proven experience (for all levels) in developing and optimizing data pipelines for machine learning, with a focus on data generation, data augmentation, or data selection techniques.

  • Technical Skills:

    • Experience with data-centric AI approaches, including data cleaning, augmentation, and synthetic data generation.

    • Strong programming skills in 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.

  • Knowledge: A strong understanding of the latest advancements in AI/ML research, particularly in data optimization (e.g. task-specific data selection, data pruning etc.). Strong analytical skills to identify and implement strategies that enhance data quality and improve model performance.

  • Collaboration & Communication: Ability to work in a highly collaborative, fast-paced startup environment and communicate complex technical concepts clearly.

 

Preferred Qualifications:

  • PhD or advanced degree in Computer Science, Machine Learning, AI, or related fields.

  • Experience building or working with large-scale data systems or platforms (e.g., distributed data pipelines, cloud-based data storage).

  • Familiarity with reinforcement learning or generative modeling techniques, particularly for data generation.

  • A passion for data-driven approaches to AI development, and the ability to translate theoretical research into actionable, scalable solutions.

 

Location

This position is based in Italy & we support relocation to Bologna, Florence or Milan for talent based abroad and interested in this role.

Why Join Us?

  • Impact: Play a key role in shaping the future of AI by developing the foundational data systems that drive innovation and optimize AI models at scale.

  • Culture: Join a highly collaborative, fast-growing team that values innovation, continuous learning, and tackling challenging real-world problems.

  • Growth: As a Series B startup, you'll have significant opportunities for personal and professional growth, with a chance to influence both product direction and technology strategy.

  • Compensation: Competitive salary, equity options, and a comprehensive benefits package.

 

How to Apply?
Please submit your resume and a brief cover letter explaining why you're excited about this opportunity, and how your experience aligns with our model compression goals.

At Axelera AI, we wholeheartedly embrace equal opportunity and hold diversity in the highest regard. Our steadfast commitment is to cultivate a warm and inclusive environment that empowers and celebrates every member of our team. We welcome applicants from all backgrounds to join us in shaping the future of AI.

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Experience

Level of experience: Senior (5-10 years)
Spoken language(s):
English
Check out the description to know which languages are mandatory.

Other Skills

  • Collaboration
  • Communication
  • Analytical Skills

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