Staff Machine Learning Engineer, Multimodal Modeling

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Staff Machine Learning Engineer, Multimodal Modeling in the United States.

This role is ideal for a senior machine learning engineer passionate about advancing multimodal AI systems. You will lead the development and fine-tuning of embedding-based retrieval models, unifying text and image representations to improve performance, generalization, and cross-modal alignment. The position requires a strong foundation in representation learning and experience applying state-of-the-art methods to real-world problems. You’ll collaborate closely with engineering and product teams to design scalable, extensible systems, while tackling complex research challenges independently. The environment is fast-paced, high-impact, and innovative, offering the opportunity to shape the future of AI-driven search and recommendation systems. Remote work flexibility is provided, with opportunities to lead and mentor others in the team.

Accountabilities:

Lead the design, development, and fine-tuning of multimodal models (e.g., CLIP, SigLIP) for embedding-based retrieval systems.
Unify and improve cross-modal representations, ensuring high performance and extensibility for evolving product use cases.
Implement and optimize model architectures, training loops, loss functions, and data pipelines for real-world applications.
Evaluate and improve vector similarity search, contrastive learning methods, and embedding quality metrics.
Collaborate with engineering teams to deploy scalable, reliable, and maintainable AI systems.
Contribute to team growth by mentoring colleagues and providing technical leadership.
Conduct research and development to explore new modeling approaches and emerging AI techniques.

Requirements:

7+ years of industry experience in machine learning, specializing in representation learning, multimodal modeling, or embedding-based retrieval.
Deep expertise in at least one domain: computer vision, natural language processing, or recommendation systems.
Proficiency in PyTorch and experience fine-tuning foundation models for real-world tasks.
Demonstrated ability to customize model architectures, training procedures, and evaluation methods.
Strong engineering skills in Python, with familiarity in Git, SQL, and Bash.
Experience with multi-GPU and distributed training workflows is a plus.
Knowledge of model compression techniques, such as distillation, quantization, or pruning, is desirable.
Ability to work independently, navigate ambiguity, and solve open-ended modeling challenges.

Benefits:

Competitive salary range of $200,000–$240,000, with equity options.
Flexible PTO and 11 company holidays.
Fully-paid health, dental, and vision benefits with HSA match.
12 weeks fully-paid parental leave, with additional physical recovery time for birthing parents.
Fertility, adoption, and surrogacy support up to $50,000 lifetime maximum.
Caregiver support programs and 1:1 equity tax advisor sessions.
Work-from-home and productivity stipends, plus home office setup support.
Access to employee resource groups and professional development opportunities.

How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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Staff Machine Learning Engineer, Multimodal Modeling

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