Research Scientist / Engineer – Performance Optimization Job at Luma AI (Palo Alto)

Research Engineer / Research Scientist - Foundations Retrieval Lead

The Foundations Research team works on high-risk, high-reward ideas that could s...

Location

United States , San Francisco

Salary:

445000.00 - 555000.00 USD / Year

OpenAI

Expiration Date

Until further notice

Requirements

Proven experience leading high-performance teams of researchers or engineers in ML infrastructure or foundational research
Deep technical expertise in representation learning, embedding models, or vector retrieval systems
Familiarity with transformer-based LLMs and how embedding spaces can interact with language model objectives
Research experience in areas such as contrastive learning, supervised or unsupervised embedding learning, or metric learning
A track record of building or scaling large machine learning systems, particularly embedding pipelines in production or research contexts
A first-principles mindset for challenging assumptions about how retrieval and memory should work for large models

Job Responsibility

Lead research into embedding models and retrieval systems optimized for grounding, relevance, and adaptive reasoning
Manage a team of researchers and engineers building end-to-end infrastructure for training, evaluating, and integrating embeddings into frontier models
Drive innovation in dense, sparse, and hybrid representation techniques, metric learning, and learning-to-retrieve systems
Collaborate closely with Pretraining, Inference, and other Research teams to integrate retrieval throughout the model lifecycle
Contribute to OpenAI’s long-term vision of AI systems with memory and knowledge access capabilities rooted in learned representations

What we offer

Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts
Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)
401(k) retirement plan with employer match
Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)
Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees
13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)
Mental health and wellness support
Employer-paid basic life and disability coverage
Annual learning and development stipend to fuel your professional growth
Daily meals in our offices, and meal delivery credits as eligible

Fulltime

Research Engineer / Research Scientist, Post-Training

The Post-Training team is responsible for training and improving pre-trained mod...

Location

United States , San Francisco

Salary:

295000.00 - 555000.00 USD / Year

OpenAI

Expiration Date

Until further notice

Requirements

Deep understanding of machine learning and machine learning applications
Working knowledge of relevant models, and building evaluations for model capability improvement
Comfortable diving into a large ML codebase to debug
Thrive in a dynamic and technically complex environment
Strong ML engineering skills and research experience, especially with novel and highly capable models
Passionate about product-driven research

Job Responsibility

Own and pursue a research agenda to improve model capability and performance
Collaborate closely with the other research and product teams, allowing customers to optimize their own models
Build robust evaluations for tracking modeling improvements
Design, implement, test, and debug code across our research stack

What we offer

Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts
Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)
401(k) retirement plan with employer match
Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)
Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees
13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)
Mental health and wellness support
Employer-paid basic life and disability coverage
Annual learning and development stipend to fuel your professional growth
Daily meals in our offices, and meal delivery credits as eligible

Fulltime

Research Scientist / Engineer – Foundation Model: Core Research

This is a rare and foundational opportunity to define the future of multimodal A...

Location

United States , Palo Alto

Salary:

250000.00 - 450000.00 USD / Year

Luma AI

Expiration Date

Until further notice

Requirements

A Bachelor's, Master's, or PhD degree in Computer Science, Machine Learning, Physics, or Mathematics is essential
A 'first-principles' intuition for scaling
Fluent in the language of frontier AI
Proven ability to design and rigorously analyze experiments and to articulate complex technical concepts effectively
Practical experience with distributed or high-performance computing environments, particularly managing and optimizing training runs on large-scale GPU clusters

Job Responsibility

Unified Modeling & Efficiency Drive the core research that powers all of Luma's products — co-designing multimodal representations, advancing core algorithms for long-context training, and establishing rigorous scaling laws to predict performance across compute budgets
Alignment & Evaluation Close the gap between training loss and user experience. Develop proxy tasks and automated metrics that serve as the compass for research decisions — ensuring our models optimize for what actually matters to users, not just benchmarks
Research Infrastructure Build the engine for high-velocity research. Maintain production-research parity, ensure reproducibility, and design systems for rapid experimentation — so that novel ideas go from hypothesis to validated result as fast as possible

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

Research Scientist Intern, Silicon Performance Architecture

Reality Labs (RL) focuses on delivering Meta's vision through AI-first devices t...

Location

United States , Redmond

Salary:

7313.00 - 12134.00 USD / Month

Research Scientist, Sensors and Systems Research

We are creating world-class consumer wearable experiences - as a member of Meta’...

Location

United States , Redmond

Salary:

122000.00 - 181000.00 USD / Year

Research Scientist, HW/SW Co-Design (PhD)

Our teams’ mission is to explore, develop and help productionize high performanc...

Location

United States , Menlo Park

Salary:

122000.00 - 181000.00 USD / Year

Senior Data Scientist - Optimization

NTT DATA is seeking a client-facing senior level Data Scientist with deep expert...

Location

United States , Remote

Salary:

144975.00 - 241265.00 USD / Year

NTT DATA

Expiration Date

Until further notice

Requirements

7+ years of experience supporting data science projects in a consulting or professional services environment
7+ years of experience across one or more of the following areas: Predictive Analytics, Data Design, Statistics, AI / Machine Learning, MLOps
2+ years of hands-on experience in Operations Research, Optimization, and Mathematical Modeling
3+ years of experience using Python, R, and/or C# to analyze disparate datasets and develop analytical solutions
Ability to travel up to 25%

Job Responsibility

Lead and deliver client-facing data science and optimization engagements, ensuring high satisfaction and measurable business outcomes
Define project objectives, scope, timelines, and success metrics in collaboration with client stakeholders and internal teams
Establish and maintain strong executive-level client relationships, gaining a deep understanding of business challenges and operational constraints
Communicate complex mathematical, optimization, and technical concepts clearly and credibly to non-technical and senior audiences
Prepare and deliver executive-ready updates, insights, and recommendations, including sensitivity analyses and scenario-based findings
Conduct market research, develop informed perspectives, and communicate thought leadership to clients and internal stakeholders
Lead the design, formulation, and delivery of operations research and optimization models for large, complex enterprises
Translate ambiguous business problems into rigorous mathematical formulations and scalable optimization solutions
Develop and refine models across domains such as: Resource allocation, Scheduling and workforce optimization, Cost and network optimization, Vehicle routing, Strategic planning (e.g., facility opening/closing, multi-period network modeling)
Apply deep expertise in optimization solvers (e.g., Gurobi preferred, CPLEX or similar) to deliver robust, production-ready solutions

Fulltime

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Research Scientist / Engineer – Performance Optimization

Job Description

Job Responsibility

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