Principal Machine Learning Engineer - Large Scale Embedding - (Remote - US)

Jobgether; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

An innovative firm is seeking a Principal Machine Learning Engineer to spearhead the development of cutting-edge recommendation systems. In this role, you will leverage advanced architectures like Graph Neural Networks and transformers to model complex data relationships. Your leadership will be pivotal in shaping the technical roadmap and collaborating with cross-functional teams to enhance machine learning pipelines. This position offers a unique opportunity to influence the future of machine learning applications at scale while mentoring a talented team. Join a forward-thinking company committed to pushing the boundaries of technology and making a significant impact in the field.

Benefits

Comprehensive healthcare benefits

401(k) match

Family planning support

Mental health benefits

Flexible vacation

Generous parental leave

Qualifications

• 15+ years of experience in machine learning and AI leadership.
• Expertise in Graph Neural Networks and recommendation systems.

Responsibilities

• Lead design and architecture of multi-entity embedding generation.
• Develop and optimize large-scale graph-based ML pipelines.

Skills

Machine Learning Leadership

Graph Neural Networks

Transformers

Python

Collaborative Filtering

Recommendation Systems

ML Frameworks (PyTorch, TensorFlow)

Tools

PyTorch Geometric

DGL

scikit-learn

Job description

Jobgether has ALL remote jobs globally. We match you to roles where you're most likely to succeed, and provide feedback on every application to help you learn. No more guesswork, application black holes, or recruiter ghosting in your job search.

For one of our clients, we are looking for a Principal Machine Learning Engineer - Large Scale Embedding, remotely from the United States.

As a Principal Machine Learning Engineer, you will lead the development of large-scale, multi-entity embeddings that drive the recommendation systems of the future. This role will focus on implementing cutting-edge architectures, such as Graph Neural Networks (GNN) and transformers, to model complex relationships within data. You will collaborate with cross-functional teams to design and scale machine learning pipelines, enabling efficient distributed training and serving. Your leadership will shape the technical roadmap and influence the future of machine learning applications at scale.

Accountabilities:

• Lead the design and architecture of multi-entity embedding generation using GNN and transformers.
• Define the technical roadmap, working with cross-functional partners to align execution plans.
• Develop and optimize large-scale graph-based machine learning pipelines for recommendation systems.
• Ensure scalable and efficient architectures for processing complex, interconnected data.
• Collaborate with internal teams to improve relevance metrics and extend the use of models in upstream functions.
• Mentor and support the growth of your team while contributing to overall product strategy.

Minimum Requirements:

• 15+ years of technical leadership experience in machine learning and AI.
• Proven ability to lead ML initiatives and communicate complex ideas effectively to cross-functional teams.
• Expertise in Graph Neural Networks, collaborative filtering, knowledge graphs, and recommendation systems.
• Strong coding proficiency in Python, with experience in ML frameworks like PyTorch Geometric, DGL, TensorFlow, and scikit-learn.
• Solid understanding of ML infrastructure components and libraries for efficient distributed training and inference.

Benefits:

• Comprehensive healthcare benefits, including medical, dental, and vision.
• 401(k) match to help secure your financial future.
• Family planning support, including gender-affirming care.
• Mental health and coaching benefits to support well-being.
• Flexible vacation and global days off to maintain work-life balance.
• Generous paid parental leave and paid volunteer time off.