Principal AI Scientist

RWS Group•Los Angeles, CA

1d•$130,000 - $170,000

About The Position

RWS Group is seeking a Principal AI Scientist to join its rapidly expanding TrainAI division — our global center of excellence, for training, evaluating, and scaling the next generation of artificial intelligence systems. TrainAI partners with some of the world's most influential technology companies to develop, refine, and optimize advanced AI models, ensuring they perform reliably across languages, domains, and real-world environments. In this role, you will define the scientific and technical strategy that underpins our AI training programs while personally building the prototypes, pilots, and production-grade tools that bring that strategy to life. You will directly contribute to the evolution of state-of-the-art large language models and intelligent systems — not just through research direction, but through hands-on engineering and experimentation. As a Principal AI Scientist, you will combine deep machine learning expertise with research leadership and builder-mindset execution. You will drive the design of robust ML methodologies, architect large-scale evaluation and benchmarking frameworks, build working MVPs that demonstrate new service capabilities, and collaborate closely with cross-functional teams to translate research advancements into scalable, production-ready AI capabilities used globally. The TrainAI division is shaping the future of artificial intelligence by uniting human insight with machine learning at enterprise scale. Our teams enable AI to better understand language, context, and culture — supporting some of the world's most sophisticated technologies. In this role, you will play a pivotal part in defining how AI systems learn, reason, and operate in the real world — and you will build the tools and systems that prove it works. About RWS TrainAI Data Services Training or fine-tuning artificial intelligence (AI) requires data. LOTS of data. However, not just any data will do – our clients need responsible AI data that’s targeted, accurate and reliable to ensure machine learning (ML) success. But preparing AI training data is a monumental task that can take up the vast majority of AI project time, leaving AI teams with precious little time to focus on developing, deploying and evaluating ML models. RWS Train AI helps our clients address this challenge head-on. With a seamless blend of technological understanding and human intelligence, RWS Train AI provides complete, end-to-end data collection and content generation, data annotation or labelling, human-in-the-loop data validation and generative AI data services for all types of AI, in any language, at any scale, based on the principles of responsible AI. Today, Train AI supports four of the world’s top five technology companies, enhancing the performance of their generative AI applications by providing services such as prompt engineering, response refinement and red teaming with locale-specific domain experts across a broad range of topic areas and educational levels.

Requirements

PhD or Master's degree in Artificial Intelligence, Machine Learning, Computer Science, Computational Linguistics, or a related field.
10+ years of experience in AI research, machine learning engineering, or applied data science.
Deep expertise in NLP, large language models, generative AI, and deep learning frameworks.
Strong programming skills (Python, PyTorch, TensorFlow, or similar) with the ability and willingness to write production-quality code, build prototypes, and debug systems hands-on.
Experience designing and deploying large-scale AI training or evaluation systems.
Track record of building working MVPs, pilots, or proof-of-concept tools — not just directing others to build them.
Demonstrated leadership in complex technical initiatives, with the ability to operate as both a strategic thinker and an individual builder.

Nice To Haves

Experience working on AI model training, alignment, or evaluation programs at or in partnership with frontier AI labs.
Hands-on experience building LLM-as-judge, automated evaluation, or hybrid human-AI quality systems.
Knowledge of human-in-the-loop AI training, RLHF, and data annotation pipelines at scale.
Background in multilingual AI, translation technologies, or global datasets.
Experience building internal tools or automation that improved operational efficiency in AI data services or annotation operations.
Publications in leading AI conferences or journals (e.g., NeurIPS, ICML, ACL, HCOMP, KDD).
Prior experience at AI data services companies (e.g., Scale AI, Appen, Labelbox, TELUS Digital) or frontier AI labs.

Responsibilities

Advance AI Data Services
Lead the development of innovative approaches to training, evaluating, and improving large language models and multimodal AI systems.
Design methodologies for large-scale data annotation, human-in-the-loop learning, and model alignment.
Apply advanced techniques in NLP, reinforcement learning, and generative AI to improve model accuracy, safety, and performance.
Conduct hands-on experimentation — running model evaluations, fine-tuning approaches, and benchmarking studies that generate publishable insights and inform client engagements.
Build Pilots, MVPs & Automated Solutions
Personally architect and build working prototypes that demonstrate new TrainAI service capabilities — such as automated evaluation pipelines, hybrid human-AI quality systems, LLM-as-judge frameworks, and domain-specific benchmarking tools.
Develop internal automation tools that improve annotation quality, reduce delivery costs, and increase operational efficiency across TrainAI programs.
Build proof-of-concept solutions for client-facing opportunities — translating technical feasibility into tangible demos that support sales conversations and RFP responses.
Own the end-to-end technical development lifecycle for pilot projects: scoping, rapid prototyping, testing, iteration, and handoff to engineering for productionization.
Create reusable frameworks, libraries, and toolkits that codify TrainAI's technical IP and enable repeatable delivery at scale.
Shape the TrainAI Research Agenda
Define scientific priorities and research initiatives that push the boundaries of AI training and evaluation.
Explore emerging techniques in AI alignment, prompt engineering, agentic systems, and model optimization.
Translate cutting-edge research into scalable solutions deployed across TrainAI programs.
Publish research papers, author white papers, and represent TrainAI at industry conferences to build market credibility and thought leadership.
Technical Authority & Leadership
Serve as the senior technical authority across the TrainAI division — the expert for AI evaluation methodology, model quality, and training science.
Act as the technical counterpart in frontier AI lab client engagements, leading solution design workshops, platform demos, and technical due diligence conversations.
Mentor data scientists, research engineers, and AI specialists — raising the technical bar across the team.
Provide architectural guidance on model pipelines, evaluation frameworks, and ML infrastructure.
Inform offering development and pricing strategy by defining what is technically feasible, defensible, and differentiated.
Cross-Functional Collaboration
Work closely with product leaders, engineering teams, and enterprise partners to operationalize AI research.
Partner with global teams to ensure AI systems perform across languages, cultures, and industries.
Collaborate with commercial teams to shape RFPs, scope technical solutions, and support client presentations with credible technical depth.
Communicate complex scientific concepts clearly to both technical and business stakeholders.
Responsible AI
Champion ethical and responsible AI development practices.
Establish standards for model evaluation, bias mitigation, explainability, and governance.
Design and implement evaluation methodologies that assess AI safety, fairness, and reliability across diverse use cases.

Benefits

Generous paid time off package, starting at 25 days per year (10 sick and 15 vacation), plus company holidays, birthday day off, paid volunteer time, and 100% paid parental leave.
401(k) Retirement plan with company match.
Company-wide agile work policy with flexible work arrangements.
Opportunities for training, professional development, and personal growth.
Smart, engaged co-workers and a global culture of diversity, innovation, and opportunity.

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