Senior Staff AI Engineer [Remote]

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

The Senior Staff AI Engineer will play a critical role in advancing next-generation artificial intelligence solutions through research, development, and production deployment of advanced machine learning systems.
This role focuses on designing, training, optimizing, and scaling complex AI models, including multimodal and reinforcement learning applications.
You will work at the intersection of AI innovation, cloud engineering, and product development to solve challenging technical problems with significant business impact.
The position requires deep expertise in machine learning architectures, distributed systems, and production-grade AI workflows.
You will collaborate with cross-functional teams to transform emerging AI capabilities into reliable, scalable solutions used in real-world environments.
This is an opportunity for a highly experienced engineer to influence strategic technology direction and contribute to advanced AI initiatives.

Accountabilities:

The Senior Staff AI Engineer will lead the development and optimization of sophisticated AI systems while providing technical leadership on complex engineering challenges. This role requires expertise in machine learning, cloud infrastructure, and production deployment, with a focus on building scalable AI solutions and improving operational workflows.

• Design, train, fine-tune, and evaluate advanced AI models, including multimodal models and large-scale machine learning systems.
• Apply parameter-efficient fine-tuning techniques such as LoRA to optimize model performance and efficiency.
• Implement reinforcement learning approaches to improve model capabilities and outcomes.
• Develop and optimize audio and speech machine learning solutions, including speaker diarization and speaker identification.
• Build high-quality training and evaluation datasets through data gathering, cleaning, validation, and curation.
• Deploy, debug, and maintain distributed AI systems in cloud environments.
• Optimize inference pipelines using techniques such as TensorRT, quantization, and pruning.
• Monitor production models, address data drift, troubleshoot failures, and improve system reliability.
• Establish and maintain continuous deployment workflows supported by unit, component, and integration testing.
• Apply advanced AI and software engineering expertise to solve complex technical challenges impacting strategic initiatives.
• Collaborate with Product and Operations teams to design and improve AI-powered workflows and solutions.
• Provide technical guidance and contribute to long-term engineering strategies and innovation initiatives.
• Apply knowledge of media management strategies, digital workflows, and content distribution processes where relevant.

Requirements:

The ideal candidate is an experienced AI engineering professional with a strong background in machine learning, cloud technologies, and enterprise software development. You should have demonstrated experience building production AI systems and the ability to operate independently on complex, high-impact technical initiatives.

• Extensive experience designing, developing, and deploying machine learning and AI solutions in production environments.
• Strong expertise in model training, optimization, evaluation, and deployment practices.
• Experience with multimodal AI models, reinforcement learning, and parameter-efficient fine-tuning techniques.
• Hands-on experience with distributed systems and cloud platforms, including 5+ years working with AWS and experience with Azure.
• Strong programming experience with languages such as Python, Java, Golang, or JavaScript.
• Experience designing software architectures using the C4 model and other traditional design frameworks.
• Strong understanding of Agile development methodologies and modern engineering practices.
• Experience with continuous integration and continuous deployment workflows.
• Familiarity with Docker, Kubernetes, and cloud-native application development is a plus.
• Knowledge of client-side technologies such as React, Angular, JavaScript, CSS, and HTML is preferred.
• Experience with broadcast production, digital media workflows, or video content management systems is a plus.
• Bachelor’s degree in Computer Science, Electrical Engineering, or equivalent practical experience required.
• Strong problem-solving skills with the ability to address ambiguous and complex technical challenges.

Benefits:

• Opportunity to work on advanced AI technologies and large-scale machine learning systems.
• Ability to influence strategic technology initiatives and innovative product development.
• Collaborative environment working with cross-functional teams across engineering, product, and operations.
• Exposure to cutting-edge AI, cloud computing, and distributed system technologies.
• Professional growth opportunities through challenging technical projects.
• Competitive compensation and comprehensive employee benefits (based on company offering).

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!

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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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.