Ai research - scientist/ engineer Job at Sentient

Senior Machine Learning Engineer (Research Scientist) - Data Foundation & AI

We build simple yet innovative consumer products and developer APIs that shape h...

Location

United States , New York

Salary:

228960.00 - 315360.00 USD / Year

Plaid

Expiration Date

Until further notice

Requirements

Strong applied ML research skills with production delivery experience
Depth in Transformers/LLMs, representation learning, or large-scale model training
Demonstrated ability to ship models to production (not just prototype)
Distributed training experience and strong Python + software engineering fundamentals
Fintech / financial data domain experience is a plus
External publications or open-source contributions is a plus

Job Responsibility

Building a foundation model on one of the world’s richest financial datasets that no one else has
Doing research that ships: moving from experimentation and prototypes to production systems serving real customers
Working across the full ML stack, from pretraining objectives and architectures to serving infrastructure and monitoring
Collaborating with a high-caliber team and seeing your work amplify the capabilities of multiple product teams
Helping hundreds of millions of consumers achieve greater financial freedom through data-driven products

Fulltime

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

Machine Learning Research Scientist / Research Engineer, Post-Training

Scale works with the industry’s leading AI labs to provide high quality data and...

Location

United States , San Francisco; Seattle; New York

Salary:

252000.00 - 315000.00 USD / Year

Scale

Expiration Date

Until further notice

Requirements

Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or a related field
Deep understanding of deep learning, reinforcement learning, and large-scale model fine-tuning
Experience with post-training techniques such as RLHF, preference modeling, or instruction tuning
Excellent written and verbal communication skills
Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals
Previous experience in a customer facing role

Job Responsibility

Research and develop novel post-training techniques, including SFT, RLHF, and reward modeling, to enhance LLM core capabilities in both text and multimodal modalities
Design and experiment new approaches to preference optimization
Analyze model behavior, identify weaknesses, and propose solutions for bias mitigation and model robustness
Publish research findings in top-tier AI conferences

What we offer

Comprehensive health, dental and vision coverage
retirement benefits
a learning and development stipend
generous PTO
equity based compensation
commuter stipend

Fulltime

Ai Research Scientist — Agentic Ai For Materials Discovery

This role sits within Meta's Reality Labs Research, in the Material and Systems ...

Location

United States , Redmond

Salary:

184000.00 - 257000.00 USD / Year

Meta

Expiration Date

Until further notice

Requirements

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
PhD in AI, Computer Science, Computational Chemistry, Materials Science, or related field
2+ years of experience with large language models, prompt engineering, or agentic AI frameworks (e.g., React, tool-use agents, multi-agent orchestration)
Demonstrated programming skills in Python and experience with ML frameworks (PyTorch, JAX, or similar)
Demonstrated experience in building end-to-end AI systems that integrate external tools and APIs
Familiarity with at least one domain: computational chemistry, molecular simulation, or materials informatics

Job Responsibility

Design, implement, and optimize LLM-orchestrated multi-agent systems for autonomous materials discovery pipelines
Build specialized AI sub-agents that operate within a closed-loop discovery framework
Integrate agentic AI workflows with computational chemistry tools (DFT, MD, Monte Carlo) and HPC infrastructure
Develop and fine-tune retrieval-augmented generation (RAG) systems over scientific literature corpora for real-time knowledge synthesis
Collaborate with materials scientists, computational chemists, and ML researchers to translate domain workflows into autonomous agent architectures
Evaluate and benchmark agent performance on materials discovery tasks — measuring accuracy, throughput, and synthetic viability of generated candidates
Contribute to open-source tooling and publish research at top-tier venues (NeurIPS, ICML, ICLR, or domain journals)

What we offer

bonus
equity
benefits

Fulltime

Ai Research Scientist —Generative Ai For Materials Discovery

Location

United States , Redmond

Salary:

154000.00 - 217000.00 USD / Year

Meta

Expiration Date

Until further notice

Requirements

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
Ph.D. degree in Machine Learning, Computational Chemistry, Materials Science, Chemical Engineering, Physics, or a closely related technical field
3+ years of research experience in generative modeling applied to molecular systems, crystal structures, or materials science (academic or industry)
Familiarity with large-scale molecular and crystal databases and data processing pipelines for chemical data
Demonstrated expertise in deep generative models — including diffusion models, flow matching / continuous normalizing flows, variational autoencoders, or autoregressive models — with applications to 3D molecular or crystal structure generation
Programming proficiency in Python with hands-on experience in PyTorch or JAX
proficiency in building, training, and evaluating large-scale deep learning models
Track record of first-author publications in top-tier ML or computational chemistry venues (e.g., NeurIPS, ICML, ICLR, JACS, Nature Computational Science, Digital Discovery)
Solid understanding of crystallography fundamentals— and molecular representations (molecular graphs, SMILES, 3D conformers)

Job Responsibility

Develop, train, and deploy generative models (diffusion models, flow matching, variational autoencoders, transformer-based architectures) for molecular and crystal structure generation, property-conditioned design, and crystal structure prediction (CSP)
Design and implement reinforcement learning and alignment strategies (e.g., physics-informed reward signals from machine-learned interatomic potentials) to steer generative models toward physically stable and synthesizable candidates
Build foundational models and scalable pretraining pipelines that unify generative and predictive learning across molecules and crystalline materials, handling both discrete atom types and continuous 3D geometries
Collaborate closely with computational chemists to integrate first-principles calculations (DFT, force fields), molecular dynamics simulations, and domain-specific constraints into generative workflows
Partner with AI agent scientists to embed generative molecular design capabilities into LLM-based multi-agent systems, enabling closed-loop autonomous experiment planning, candidate generation, and decision making
Curate, preprocess, and manage large-scale molecular and crystal structure datasets for model training and benchmarking
Establish rigorous evaluation frameworks — measuring validity, novelty, uniqueness, stability, and synthesizability of generated structures — and benchmark against state-of-the-art methods
Contribute to the architecture and roadmap of the autonomous materials-discovery platform, ensuring generative design modules interface seamlessly with robotic workcells, characterization instruments, and data infrastructure

What we offer

bonus + equity + benefits

Fulltime

AI Research Scientist - Voice AI Team, Meta Superintelligence Labs

Meta is seeking AI Research Scientists to join the Realtime AI Voice team in Met...

Location

United States , Menlo Park, CA +2 locations

Salary:

184000.00 - 257000.00 USD / Year

Meta

Expiration Date

Until further notice

Requirements

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
PhD degree in Computer Science, Mathematics, or similar quantitative field
2+ years of post-PhD experience in an academic, industry, or government laboratory setting, with primary responsibilities focused on AI research
Proven track record of publications at peer-reviewed AI & speech conferences (e.g. NeurIPS, ICML, ICLR, ICASSP)
Experience in training, fine-tuning, and/or experimenting with foundation models beyond black-box use
Familiarity with one or more deep learning frameworks (e.g., pytorch, tensorflow)
Experience communicating complex research to public audiences of peers

Job Responsibility

Lead, collaborate, and execute on research that pushes forward the state of the art in speech and large language model research
Directly contribute to experiments, including designing experimental details, develop reusable code, running evaluations, and organizing results
Help identify long-term research goals as well as intermediate milestones
Work cross-functionally to translate research breakthroughs into scalable, production-ready solutions for Meta's conversational AI / product experiences

What we offer

bonus
equity
benefits

AI Research Scientist, MRS AI (PhD)

The AI Research Scientist role conducts cutting-edge research and develops advan...

Location

United States , Menlo Park

Salary:

122000.00 - 181000.00 USD / Year

Meta

Expiration Date

Until further notice

Requirements

Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta
Currently has, or is in the process of obtaining a PhD degree in Computer Science, Artificial Intelligence, Data Science, or related technical fields
Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment

Job Responsibility

Collaborate, and execute on research that pushes forward the state of the art in large language model research
Directly contribute to experiments, including designing experimental details, running evaluations, and organizing results
Contribute to publications and open-sourcing efforts
Help identify long-term research goals as well as intermediate milestones
Prioritize research that can be applied to Meta's product development

What we offer

bonus
equity
benefits

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