Machine Learning Engineer at Jobgether – United States

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

This role offers the opportunity to lead high-impact AI and ML initiatives that directly influence critical decision systems. You will design and implement advanced deep learning architectures, bridging the gap between research and production-grade financial systems. The position involves solving complex, ambiguous problems, collaborating with cross-functional teams, and ensuring models are optimized for scalability, efficiency, and measurable business outcomes. You will mentor peers, contribute to technical standards, and help shape the function’s AI capabilities. This is a highly autonomous role for individuals passionate about pushing the boundaries of applied ML in a dynamic environment. Ideal candidates are technically deep, analytically rigorous, and adept at translating research into practical, high-impact solutions.

• Lead and execute applied ML research projects, developing architectures such as Transformers, Graph Neural Networks, and multimodal models for critical production systems.

• Translate research into scalable, efficient production solutions, addressing latency, interpretability, and cost constraints.

• Collaborate with cross-functional teams including Data, Infrastructure, and Product to solve complex modeling problems and deliver innovative AI-driven solutions.

• Establish and maintain technical standards for model experimentation, evaluation, and code quality within the AI Core team.

• Mentor senior engineers and researchers, guiding deep learning practices, problem formulation, and research methodologies.

• Contribute to the growth and strategy of the ML function through hiring, internal task forces, and thought leadership initiatives.

Requirements:

• 5–7+ years of experience in applied AI/ML, with a record of deploying research-driven models into production.

• Deep expertise in deep learning architectures such as Transformers, GNNs, or multimodal models.

• Proficiency in Python and frameworks like PyTorch, TensorFlow, or JAX.

• Solid understanding of MLOps and deployment constraints at scale.

• Strong analytical skills, including experience with large-scale experimentation and A/B testing.

• Exceptional problem-solving skills, capable of navigating ambiguity and messy data.

• Excellent communication skills to convey complex technical concepts to both technical and non-technical stakeholders.

Benefits:

• Opportunity to earn equity in the company.

• Medical, dental, and vision insurance.

• Life insurance and AD&D coverage.

• Extended maternity and paternity leave.

• Access to learning and development platforms, including technical and language courses.

• Mental health and wellness assistance programs.

• 401(k) and savings plan options (HSA/FSA).

• Work-from-home allowance and potential relocation assistance.