Machine Learning Scientist 4 - Generative Models, Evaluation

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Machine Learning Scientist 4 - Generative Models, Evaluation based in United States.

This is a senior machine learning research role focused on advancing generative AI and improving how AI-generated content is evaluated at scale.

You will help shape algorithmic strategies that influence how content is promoted and discovered by millions of members.

The role combines applied research, model development, experimentation, and production-oriented problem solving.

You will work on challenging problems involving LLMs, summarization, generated-text quality, and AI-based evaluation systems.

As a technical leader, you will identify promising advances in generative AI and translate them into high-impact business applications.

You’ll collaborate with experienced scientists and engineers in a highly innovative, cross-functional environment.

The position offers the opportunity to influence both the technical direction of the field and the future of content discovery.

Accountabilities:

• Advance generative AI research: Monitor the latest developments in LLMs, generative models, and related research, identifying techniques with potential to solve meaningful business and product challenges.
• Develop advanced ML solutions: Apply state-of-the-art machine learning and deep learning approaches to problems such as summarization quality, generated-content assessment, and automated evaluation.
• Build LLM-based evaluators: Research and develop AI-powered “judge” systems capable of assessing whether generated content meets defined quality standards and improving evaluation reliability.
• Own end-to-end experimentation: Lead the full machine learning development lifecycle, from research and hypothesis formation through model training, experimentation, statistical analysis, evaluation, and iteration.
• Translate research into applications: Partner closely with machine learning scientists and engineers to integrate models into scalable business applications and technology platforms.
• Shape technical strategy: Serve as a subject matter expert, identifying high-value opportunities, defining technical roadmaps, and influencing strategic decisions across multidisciplinary teams.
• Communicate complex ideas: Translate sophisticated ML and generative AI concepts into clear recommendations and insights for both technical and non-technical stakeholders.
• Contribute to the ML community: Engage with internal and external research communities by sharing knowledge, learning from emerging work, and contributing to a culture of technical excellence and innovation.

Requirements:

• Demonstrated experience following advances in LLMs and generative AI research, with the ability to distinguish promising developments from those that are less applicable to real-world business problems.
• Strong foundations in machine learning and deep learning, particularly in natural language processing, natural language understanding, and text generation.
• Research or applied experience in summarization, generated-text evaluation, LLM-as-a-judge methodologies, or related evaluation techniques is highly valuable.
• Familiarity with vision-based generative models, including diffusion models, is a plus.
• Expertise in one or more LLM post-training approaches and an understanding of modern techniques for improving generative model performance.
• Proven ability to design, execute, and analyze rigorous ML experiments, including hypothesis development, controlled experimentation, statistical validation, and interpretation of results.
• Strong research mindset combined with the ability to connect technical innovation to practical product or business outcomes.
• Excellent communication and collaboration skills, with the ability to influence technical strategy and work effectively across scientific, engineering, and business functions.
• Ability to operate independently, identify high-impact opportunities, and take ownership of complex problems from initial research through implementation.

Benefits:

• Annual compensation range: $300,000-$537,000, with the range varying according to location, job family, background, skills, and experience.
• Flexible compensation structure: Compensation is generally provided through annual salary, with the option to determine the preferred balance between salary and stock options each year.
• Health coverage: Comprehensive health plans, including support for physical and mental health.
• Financial benefits: 401(k) retirement plan with employer match and stock option program.
• Health accounts: Health Savings Accounts and Flexible Spending Accounts.
• Protection benefits: Disability programs, life insurance, and serious injury benefits.
• Family support: Family-forming benefits designed to support employees through different stages of family life.
• Time off: Paid leave programs, with salaried employees receiving flexible time off.
• Remote work: Full-time remote position within the United States.
• Inclusive environment: Commitment to diversity, inclusion, equal opportunity, and meaningful candidate and employee experiences.