Senior Machine Learning Engineer

Job Description

AtHumanoid, we strive to create the world's leading, commercially scalable, safe, and advanced humanoid robots that seamlessly integrate into daily life and amplify human capacity.

In a world where artificial intelligence opens up new horizons, our faith in its potential unveils a new outlook where, together, humans and machines build a new future filled with knowledge, inspiration, and incredible discoveries. The development of a functional humanoid robot underpins an era of abundance and well-being where poverty will disappear, and people will be able to choose what they want to do. We believe that providing a universal basic income will eventually be a true evolution of our civilization.

As the demands on our built environment rise, labor shortages loom. With the world’s workforce increasingly moving away from undesirable tasks, the manufacturing, construction, and logistics industries critical to our daily lives are left exposed. By deploying our general-purpose humanoid robots in environments deemed hazardous or monotonous, we envision a future where human well-being is safeguarded while closing the gaps in critical global labor needs.

Responsibilities:

1. Perform data exploration to identify patterns, anomalies, and distributions within datasets.
2. Conduct descriptive statistical analyses to derive actionable insights.
3. Integrate data from multiple sensors and sources for cohesive and comprehensive analysis.
4. Apply data preprocessing techniques, including normalization, transformation, filtering, and cleaning, to ensure quality and accuracy.
5. Collaborate with cross-functional teams to design and manage data collection projects.
6. Ensure data consistency and integrity throughout the project lifecycle.
7. Develop reports and visualizations to effectively communicate findings and insights to stakeholders.
8. Provide data-driven recommendations to support informed decision-making across teams.
9. Contribute to fine-tuning large foundational models for advanced applications.

Requirements:

1. Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Engineering, or a related field.
2. Proficiency in Python, PyTorch, SQL, and experience in training Deep Neural Networks (DNNs), preferably transformer models.
3. Strong knowledge of statistical methods, anomaly detection, and data visualization tools.
4. Hands-on experience with sensor data processing, integration, and analysis.
5. Excellent analytical and problem-solving skills.
6. Strong communication skills to effectively present data insights and recommendations.
7. Ability to manage and prioritize multiple projects in a fast-paced and dynamic environment.

Bonus Qualifications:

1. Experience managing data for training Visual Models (VLM), Visual Action (VLA) models, and transformer-based policy and value functions.
2. Familiarity with flow matching algorithms in the context of robotic actions or similar applications.
3. Hands-on experience with PyTorch Fully Sharded Data Parallel (FSDP).
4. Experience using Hugging Face models for inference, fine-tuning, and training.
5. Expertise in diffusion techniques and flow matching algorithms, particularly in training policies based on these methods.

Benefits:

1. High competitive salary.
2. 23 calendar days of vacation per year.
3. Flexible working hours.
4. Opportunity to work on the latest technologies in AI/ML, Robotics, and others.
5. Startup model, offering a dynamic and innovative work environment.

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