Applied AI Researcher, Post-Training Job at Distyl AI (San Francisco)

Research Scientist Intern, AI Research Multi-modal Post-Training

Meta is seeking Research Scientist Interns in the Meta Superintelligence org. We...

Location

United States , Menlo Park

Salary:

7650.00 - 12134.00 USD / Month

Member of Technical Staff - Post-Training

This Microsoft AI Superintelligence Post-Training team is dedicated to advancing...

Location

United States , Redmond

Salary:

84200.00 - 199000.00 USD / Year

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Bachelor's Degree (complete or in progress) in relevant field AND 3+ months related research internship experience OR Master's Degree in relevant field OR equivalent experience
Software engineering skills with fluency in Python and modern data libraries
The ability to meet Microsoft, customer and/or government security screening requirements are required for this role
These requirements include but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter

Job Responsibility

Design & Evaluate Datasets – Build high-quality datasets and benchmarks for training AI models
run ablation studies to measure impact and optimize data effectiveness
Advance Model Training – Apply deep expertise in pre-training, post-training, and reinforcement learning (RL) for both language and multimodal models
Develop Data Infrastructure – Create and maintain scalable pipelines for ingestion, preprocessing, filtering, and annotation of large, complex datasets
Data Quality & Analysis – Assess real-world multimodal datasets (text, image, video, audio, code) for quality, diversity, and relevance
identify gaps and propose improvements
Tooling & Workflows – Build lightweight tools for dataset auditing, visualization, and versioning to streamline experimentation
Research & Innovation – Collaborate with cross-functional teams to push research and product boundaries, delivering models that make a real-world impact
Embody our Culture and Values

Fulltime

Member of Technical Staff - Post-Training

This Microsoft AI Superintelligence Post-Training team is dedicated to advancing...

Location

United States , Redmond

Salary:

119800.00 - 234700.00 USD / Year

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Doctorate in relevant field OR equivalent experience
Software engineering skills with fluency in Python and modern data libraries
The ability to meet Microsoft, customer and/or government security screening requirements are required for this role
These requirements include but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter

Job Responsibility

Design & Evaluate Datasets – Build high-quality datasets and benchmarks for training AI models
run ablation studies to measure impact and optimize data effectiveness
Advance Model Training – Apply deep expertise in pre-training, post-training, and reinforcement learning (RL) for both language and multimodal models
Develop Data Infrastructure – Create and maintain scalable pipelines for ingestion, preprocessing, filtering, and annotation of large, complex datasets
Data Quality & Analysis – Assess real-world multimodal datasets (text, image, video, audio, code) for quality, diversity, and relevance
identify gaps and propose improvements
Tooling & Workflows – Build lightweight tools for dataset auditing, visualization, and versioning to streamline experimentation
Research & Innovation – Collaborate with cross-functional teams to push research and product boundaries, delivering models that make a real-world impact
Embody our Culture and Values

Fulltime

Research Engineer / Scientist - Post-training

At Luma, the Post-training team is responsible for unlocking creative control in...

Location

United States , Palo Alto

Salary:

187500.00 - 395000.00 USD / Year

Luma AI

Expiration Date

Until further notice

Requirements

Advanced degree (Master's or PhD) in Computer Science, Artificial Intelligence, Machine Learning, or related technical discipline with concentrated study in deep learning and computer vision methodologies
Demonstrated ability to do independent research in Academic or Industry settings
Substantial industry experience in large-scale deep learning model training, with demonstrated expertise in at least one of Large Language Models, Vision-Language Models, Diffusion Models, or comparable generative AI architectures
Comprehensive technical proficiency and practical experience with leading deep learning frameworks, including advanced competency in one of PyTorch, JAX, TensorFlow, or equivalent platforms for model development and optimization
Strong orientation toward applied AI implementations with emphasis on translating product requirements into technical solutions, coupled with exceptional visual discrimination and dedicated focus on enhancing visual fidelity and aesthetic quality of generated content
Proficiency in accelerated prototyping and demonstration development for emerging features, facilitating efficient iteration cycles and comprehensive stakeholder evaluation prior to production implementation
Established track record of effective cross-functional teamwork, including successful partnerships with teams spanning Product, Design, Evaluation, Applied, and creative specialists

Job Responsibility

Optimize Luma's image and video generative models through targeted fine-tuning to improve visual quality, instruction adherence, and overall performance metrics
Implement reinforcement learning techniques including Direct Preference Optimization and Generalized Reward Preference Optimization to align model outputs with human preferences and quality standards
Partner closely with the Applied Research team to identify product requirements, understand diverse use cases across Luma's platforms, and execute targeted fine-tuning initiatives to address performance gaps and enhance user-facing capabilities
Conduct comprehensive side-by-side evaluations comparing model performance against leading market competitors, systematically analyzing the impact of post-training techniques on downstream performance metrics and identifying areas for improvement
Develop advanced post-training capabilities for Luma’s video models including Camera control, Object & character Reference, Image & Video Editing, Human Performance & Motion Transfer Approaches
Architect data processing pipelines for large-scale video and image datasets, implementing filtering, balancing, and captioning systems to ensure training data quality across diverse content categories
Research and deploy cutting-edge diffusion sampling methodologies and hyperparameter optimization strategies to achieve superior performance on established visual quality benchmarks
Research emerging post-training methodologies in generative AI, evaluate their applicability to Luma's product ecosystem, and integrate promising techniques into our Post-training recipe

Fulltime

Ai Research Scientist, Video Generation And Post Training, Fair

Meta is seeking a Research Scientist to join the Fundamental AI Research (FAIR) ...

Location

United States , Menlo Park

Salary:

154000.00 - 217000.00 USD / Year

Research Scientist, Safety Post Training

As the leading data and evaluation partner for frontier AI companies, Scale play...

Location

United States , San Francisco, CA; New York, NY

Salary:

216000.00 - 270000.00 USD / Year

Scale

Expiration Date

Until further notice

Requirements

Experience with post-training and RL techniques such as RLHF, DPO, GRPO, and similar approaches
A track record of published research in machine learning, particularly in generative AI
At least three years of experience addressing sophisticated ML problems, whether in a research setting or in product development
Strong written and verbal communication skills to operate in a cross-functional team

Job Responsibility

Develop and apply post-training methods and interpretability techniques to make frontier AI systems safer, and better understood by researchers and policymakers
Design and run post-training pipelines to study how training choices affect model safety, robustness, and alignment properties
Develop interpretability-informed evaluations that reveal how and why models produce unsafe, deceptive, or otherwise undesirable behaviors, and use those insights to guide targeted mitigations
Collaborate with policymakers, engineers, and other researchers to translate post-training and interpretability findings into actionable safety standards, evaluation benchmarks, and best practices

What we offer

comprehensive health, dental and vision coverage
retirement benefits
learning and development stipend
generous PTO
commuter stipend (eligible)

Fulltime

AI Applied Scientist - PhD Intern, Foundational AQ & EQ

As a PhD Research Intern on the AQ/EQ Foundation team, you will conduct state-of...

Location

United States

Salary:

104000.00 - 166000.00 USD / Year

Zillow

Expiration Date

Until further notice

Requirements

Currently enrolled in a PhD program in Computer Science, Machine Learning, Artificial Intelligence, or a related field with a strong publication record
Advanced research in natural language processing (NLP) and/or reinforcement learning (RL)
Practical experience fine-tuning and adapting large language models (LLMs) for specific use cases
Familiarity with the design and implementation of automated/ agentic workflows
Deep understanding of LLMs, hands on experience of post-training with the most popular OSS models
Proficiency in Python and modern ML frameworks (e.g., PyTorch, TensorFlow)
Excited about applying advanced AI methods to impactful, real-world problems
Strong communication skills and ability to work collaboratively in a multidisciplinary environment
Strong research mindset, with motivation to publish

Job Responsibility

Researching and developing techniques for fine-tuning LLMs with domain-specific data
Applying reinforcement learning to optimize model performance for user-centric outcome
Designing and prototyping agentic workflows that can autonomously perform tasks and assist home buyers
Collaborating with cross-functional teams to evaluate and deploy research prototypes
Sharing insights through presentations, documentation, and potentially publications

Fulltime

Senior Applied AI Engineer

We are on a mission to ensure everyone has access to medical expertise, no matte...

Location

Denmark , København

Salary:

Not provided

Life Science Talent

Expiration Date

Until further notice

Requirements

Strong programming skills in Python and the ability to contribute to production-grade codebases
Hands-on experience in LLMs, including at least some of the following: Training, finetuning, or post-training transformer-based models
Building or operating LLM inference services in production, including performance work
Experience with embeddings, vector databases, and semantic search
Practical experience implementing RAG architectures
Designing robust evaluations for agent workflows and generative systems, including metrics, error analysis, and human evaluation methods
Experience building production-graded ML systems that can be deployed and operated, including pipelines, CI and CD practices, and monitoring
Strong product mindset with the ability to translate ideas into working systems
Clear communication and collaboration skills across research, engineering, and product
A Master’s degree in computer science, engineering, mathematics, statistics, physics, or a related field, or equivalent professional experience

Job Responsibility

Design and build LLM-powered product features used in production
Develop agentic workflows and frameworks that coordinate multiple AI components
Implement RAG (Retrieval-Augmented Generation) architectures using embeddings and vector search
Build systems for prompting, context engineering, and tool usage
Develop evaluation frameworks to measure LLM and agent performance
Work closely with product and platform teams to turn AI capabilities into reliable, scalable product features
Continuously improve system reliability, latency, and cost efficiency of AI pipelines

What we offer

Equipment provided by Corti

Fulltime

Select Country

Applied AI Researcher, Post-Training

Job Description

Job Responsibility

Requirements

What we offer

Looking for more opportunities?