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

We are seeking an experienced AI professional to bridge advanced research and real-world machine learning applications.
This role combines scientific exploration with hands-on engineering to design, test, and deploy impactful AI solutions.
You will work across areas such as natural language processing, computer vision, recommendation systems, and structured data.
The position offers the opportunity to influence AI strategy while solving complex business challenges through innovative technology.
You will collaborate with multidisciplinary teams to move ideas from experimentation into scalable production systems.
This is an ideal opportunity for someone passionate about modern AI research, responsible deployment, and building the next generation of intelligent solutions.

As a Research Scientist – AI, you will contribute to the full lifecycle of AI development, from research and experimentation to production deployment and continuous improvement. You will help define technical approaches, evaluate emerging technologies, and ensure AI systems deliver measurable value while maintaining reliability, scalability, and responsible practices.

• Design, prototype, and evaluate applied AI solutions across domains including natural language, computer vision, recommendation systems, and structured data.
• Translate complex and ambiguous business challenges into well-defined machine learning problems with clear objectives and evaluation criteria.
• Research and assess emerging advancements in deep learning, large language models, and related AI fields to identify practical applications.
• Develop rigorous experimentation processes, including benchmarking, ablation studies, and statistical evaluation methodologies.
• Build production-ready machine learning pipelines using modern frameworks, tools, and infrastructure.
• Collaborate with engineering teams to optimize model performance, including accuracy, latency, scalability, and cost efficiency.
• Create tools and processes for dataset development, labeling, validation, and ongoing data quality monitoring.
• Partner with product and domain teams to ensure AI solutions align with user needs, business goals, and responsible AI principles.
• Implement model safety, fairness, and reliability evaluations to guide technology decisions.
• Document research outcomes, technical decisions, and operational processes for both technical and non-technical stakeholders.
• Mentor engineering teams on applied machine learning practices, evaluation methods, and responsible AI deployment.
• Contribute to AI roadmap development through research insights, technical expertise, and identification of emerging opportunities.

The ideal candidate combines deep AI research knowledge with strong software engineering capabilities and the ability to transform innovative concepts into practical solutions. You should be comfortable working independently, collaborating across teams, and communicating complex technical ideas clearly.

• Master’s or PhD degree in Computer Science, Machine Learning, Statistics, or a related technical discipline, or equivalent applied experience.
• 6+ years of experience across AI research, machine learning engineering, or applied ML development.
• Strong programming skills in Python and experience with modern machine learning frameworks such as PyTorch or JAX.
• Hands-on experience training, fine-tuning, and evaluating advanced deep learning models at scale.
• Strong understanding of mathematical, statistical, and theoretical foundations of machine learning.
• Experience taking ML models from research prototypes through production deployment.
• Familiarity with distributed training, mixed-precision training, and accelerator-based computing environments.
• Ability to analyze and adapt techniques from current AI research publications.
• Strong written and verbal communication skills with the ability to explain complex concepts effectively.
• Demonstrated success delivering impactful AI projects in practical environments.

Preferred qualifications include:

• Published research in recognized AI or machine learning conferences.
• Experience with large language model training, fine-tuning, or evaluation.
• Knowledge of retrieval-augmented generation, agent-based AI systems, or multimodal architectures.
• Experience with responsible AI practices, model evaluation, and alignment techniques.
• Contributions to open-source machine learning projects.

• Competitive annual salary range of $100,000–$150,000 depending on experience and qualifications.
• Fully remote work opportunity across the United States.
• Full-time direct employment opportunity.
• Opportunity to work on advanced AI initiatives with meaningful real-world impact.
• Career growth potential within an innovative technology environment.
• Exposure to cutting-edge machine learning research, tools, and engineering practices.
• Collaborative culture focused on innovation, knowledge sharing, and professional development.
• Equal opportunity workplace committed to fostering an inclusive environment.