Senior Applied Scientist – Model Training, Optimization

Dream

. Develop training and post-training methods, including reinforcement learning, distillation, and automated optimization, to improve model capability and efficiency .

Posted 10/25/2026full-timeTel Aviv • IsraelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive expertise in AI/ML model training and optimization, with a strong focus on reinforcement learning, distillation, and large-scale training experiments. Proficient in Python and frameworks like PyTorch or JAX, with a solid foundation in research methodologies and data-driven decision-making.

Highest-signal resume keywords

AI/ML ExperienceModel Training ExpertisePython ProficiencyPyTorch or JAX ProficiencyCurriculum Design Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Reinforcement LearningDistillationAutomated OptimizationData MixingExperiment LoggingAblation StudiesModel ArchitecturesTraining DynamicsDebugging Large-Scale PipelinesData Quality Investigation

Soft Skills

Independent OwnershipEmpirical DisciplineClear JudgmentMentoring

Certifications & Qualifications

MSc or PhD in Relevant Field

Industry Keywords

Audio UnderstandingSpeech UnderstandingTraining ExperimentsCompute EfficiencyConvergence Challenges

Tech Stack

Tools & technologies

PythonPyTorch

About the role

Key responsibilities & impact

Develop training and post-training methods, including reinforcement learning, distillation, and automated optimization, to improve model capability and efficiency
Design data mixtures, sampling strategies, and curricula
Investigate how data quality and composition drive performance
Run and debug large-scale training experiments
Address convergence, stability, and compute efficiency challenges
Adapt architectures and learning methods to new tasks and modalities, including audio and speech understanding
Own problems end to end, including definition, experimentation, and validation
Use rigorous benchmarks, ablations, and reproducible results to drive decisions
Partner with engineering through deployment
Raise risks early and challenge ideas constructively
Take on difficult research problems
Mentor fellow researchers

Requirements

What you’ll need

8+ years of hands-on AI/ML experience
Experience owning multiple projects from problem definition to real-world impact
Deep expertise in model training, with hands-on experience in one or more of post-training, reinforcement learning, distillation, or predictive ML
MSc or PhD in a relevant field, or equivalent demonstrated research accomplishments
Strong research foundations
Proficiency in Python
Proficiency in PyTorch or JAX
Experience building and debugging large-scale training and evaluation pipelines
Deep command of model architectures and training dynamics
Ability to diagnose failures and balance quality, stability, and efficiency
Experience with data mixing, curriculum design, experiment logging, and ablation studies
Independent ownership, empirical discipline, and clear judgment through complex training cycles and deployment constraints
Research experience in audio or speech is an advantage

Benefits

Comp & perks

Full-time employment
Opportunity to work at a global scale alongside AI researchers, cyber operators, and government experts
Work on sovereign AI and national cyber-defense projects with potential impact on billions of people
Autonomy to choose approaches and own problems end to end
Mentorship opportunities
Industry and military R&D backgrounds equally valued