Staff Machine Learning Engineer in United States Embassy at Jobgether

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff Machine Learning Engineer based in United States.

This role offers the opportunity to build and scale advanced machine learning solutions that directly impact a rapidly evolving technology platform.
You will join a highly autonomous engineering environment focused on solving complex real-world problems through AI and data-driven innovation.
The position combines deep technical expertise with ownership of ML systems from experimentation through production deployment.
You will collaborate with cross-functional teams to transform customer challenges into reliable, scalable solutions.
Working with large-scale document processing systems and modern ML technologies, you will help shape the future of intelligent automation.
This is an ideal opportunity for an experienced engineer who thrives on technical leadership, continuous improvement, and impactful engineering work.

The Staff Machine Learning Engineer will lead the design, development, and operation of production-scale machine learning systems while driving technical excellence across engineering initiatives. This role requires strong ownership, collaboration, and the ability to translate complex technical challenges into business value.

• Design, build, deploy, and optimize machine learning models that process large volumes of complex, unstructured data.
• Develop and maintain scalable ML pipelines capable of supporting millions of documents and diverse customer requirements.
• Lead technical initiatives from early experimentation through production implementation and ongoing improvement.
• Create reliable model deployment strategies while ensuring performance, scalability, and operational stability.
• Improve ML system accuracy, efficiency, and latency through advanced techniques such as deep learning, transfer learning, and model optimization.
• Partner with product managers, engineers, and business stakeholders to understand customer needs and deliver impactful AI solutions.
• Establish and promote ML engineering standards, best practices, and repeatable development processes across teams.
• Influence technical decisions and contribute to architectural direction for machine learning platforms.
• Support production systems by applying reliability engineering principles and proactively resolving technical challenges.
• Communicate technical trade-offs, risks, and opportunities clearly across technical and non-technical teams.

The ideal candidate is an experienced machine learning engineer with a strong background in production ML systems, distributed architectures, and collaborative technical leadership.

• 10+ years of software engineering experience, including 4+ years working with production machine learning systems at scale.
• Proven experience designing, deploying, and operating distributed machine learning systems.
• Strong understanding of ML model deployment patterns, data pipelines, and production reliability practices.
• Experience working with programming languages such as Python and familiarity with ML-focused technologies and frameworks.
• Experience with machine learning tools and platforms such as PyTorch, HuggingFace, AWS SageMaker, or similar technologies is preferred.
• Ability to work with large-scale data processing systems and complex, noisy datasets.
• Strong problem-solving skills with a data-driven approach to evaluating solutions and making technical decisions.
• Demonstrated ability to influence engineering practices and technical direction across teams.
• Excellent communication skills with the ability to collaborate effectively in a remote environment.
• Curiosity, empathy, adaptability, and a continuous learning mindset.

• Annual salary range of $206,261 - $330,017.
• Fully remote work opportunity within eligible U.S. locations.
• Comprehensive medical, dental, and vision insurance coverage.
• Paid time off and employee wellness support.
• 401(k) retirement plan.
• Access to modern engineering tools and a high-performance development environment.
• Company-provided top-tier equipment, including a professional laptop setup.
• Opportunity to work on impactful AI/ML systems at significant scale.
• Collaborative culture focused on innovation, learning, and continuous improvement.