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Machine Learning Engineer
Location
United States
Posted
3 days ago
Salary
Not specified
No structured requirement data.
Job Description
Role Description
This role offers the opportunity to design and deploy cutting-edge AI and machine learning solutions that drive critical decision-making processes in large-scale digital financial systems. The Machine Learning Engineer will work on applied research projects, building and optimizing advanced architectures such as Transformers, GNNs, and multimodal models for production environments. You will collaborate with cross-functional teams to translate complex research into scalable, efficient, and cost-effective solutions that deliver measurable business impact. The position emphasizes autonomy, technical leadership, and innovation while contributing to the growth and expertise of the AI function. Ideal candidates thrive on solving ambiguous challenges, mentoring peers, and shaping the future of AI-driven financial products. The environment supports high-impact work in a collaborative and forward-thinking team.
- Lead and execute applied research initiatives, focusing on designing architectures deployable across critical business use cases.
- Solve complex, ambiguous ML problems, coordinating with Data, Infrastructure, and Product teams to deliver innovative solutions.
- Bridge research and production by ensuring models are optimized for latency, interpretability, scalability, and cost-efficiency.
- Collaborate cross-functionally to integrate AI solutions into downstream decision systems.
- Establish technical standards for experimentation, model evaluation, and code quality within the AI team.
- Mentor senior engineers and researchers, providing guidance on deep learning methodologies and best practices.
- Contribute to internal thought leadership through papers, presentations, or research collaborations aligned with strategic goals.
Qualifications
- 5–7+ years of experience in applied AI/ML with proven success deploying research-driven systems into production.
- Deep expertise in Deep Learning architectures, including Transformers, Graph Neural Networks, and multimodal models.
- Strong programming skills in Python and proficiency with ML frameworks like PyTorch, JAX, or TensorFlow.
- Solid understanding of MLOps practices and constraints for production-scale models.
- Experience with large-scale experimentation, A/B testing, and problem formulation in complex or ambiguous datasets.
- Excellent communication skills to convey technical concepts to both technical and non-technical stakeholders.
- Ability to collaborate across teams and provide mentorship to peers and junior engineers.
Benefits
- Competitive salary with potential equity opportunities.
- Comprehensive medical, dental, and vision insurance.
- Life insurance and AD&D coverage.
- Extended maternity and paternity leave programs.
- Learning and development programs, including internal courses and language learning initiatives.
- Mental health and wellness support.
- 401(k) retirement plans and health savings options.
- Work-from-home allowance and relocation assistance if applicable.
Job Requirements
- 5–7+ years of experience in applied AI/ML with proven success deploying research-driven systems into production.
- Deep expertise in Deep Learning architectures, including Transformers, Graph Neural Networks, and multimodal models.
- Strong programming skills in Python and proficiency with ML frameworks like PyTorch, JAX, or TensorFlow.
- Solid understanding of MLOps practices and constraints for production-scale models.
- Experience with large-scale experimentation, A/B testing, and problem formulation in complex or ambiguous datasets.
- Excellent communication skills to convey technical concepts to both technical and non-technical stakeholders.
- Ability to collaborate across teams and provide mentorship to peers and junior engineers.
Benefits
- Competitive salary with potential equity opportunities.
- Comprehensive medical, dental, and vision insurance.
- Life insurance and AD&D coverage.
- Extended maternity and paternity leave programs.
- Learning and development programs, including internal courses and language learning initiatives.
- Mental health and wellness support.
- 401(k) retirement plans and health savings options.
- Work-from-home allowance and relocation assistance if applicable.
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