Raydar Logo

Raydar

Machine Learning Research Scientist

Posted 2 Days Ago
Be an Early Applicant
In-Office
San Mateo, CA, USA
200K-450K Annually
Entry level
In-Office
San Mateo, CA, USA
200K-450K Annually
Entry level
Develop research systems using neural networks, reinforcement learning, and post-training for large language models. Collaborate with leadership and software engineers to test ideas, refine prototypes, and ship dependable production software. The role involves automating research workflows, tracking AI developments, and independently exploring open research directions. Candidates should have advanced academic or industry research experience, publications or comparable achievements, strong Python skills, and experience with reward-driven training, fine-tuning, and large-scale machine learning systems.
The summary above was generated by AI

About the company

Our client is a technology company.

The role

Raydar is recruiting for this role on behalf of our client. Develop research systems that propose, test and refine ideas, then move the most promising ones from prototype into shipped software. The position mixes neural network development, reinforcement learning and close work with engineers.

What you'll do

- Work closely with leadership to develop systems that propose, test and refine ideas.

- Team up with software engineers to turn experimental methods into dependable, shipped software.

- Apply reinforcement learning and post-training to large language models to automate parts of the research workflow.

- Keep up with new developments in AI research and automation.


Requirements

What we're looking for

- MS or PhD in computer science, machine learning, AI or a quantitative field, or equivalent research experience.

- Record of publishing in leading AI venues, or comparable experience at an industry research lab.

- Proficiency developing neural network models with gradient-based and reward-based methods, beyond wrapping hosted LLM APIs.

- Post-training or reinforcement learning work on large language models of 15B+ parameters, agent models or genetic algorithms.

- Strong Python skills, with the ability to ship production code independently.

- Track record applying reward-driven training and fine-tuning to neural models.

- Self-directed, comfortable exploring open research directions with minimal supervision.

Bonus points

- Experience at a frontier AI lab or top AI research team.

- Peer-reviewed papers in well-regarded machine learning venues.

- Background operating large multi-accelerator compute jobs or machine learning pipelines at scale.

- Background or interest in automated scientific research.

- Degree from a top-20 institution.


Benefits

Compensation and benefits

- Salary: $200K - $450K

- Equity

- Flexible time off

Location and work model

- San Mateo, CA, United States

- Hybrid, 4 days in-office

- Full-time

Similar Jobs

3 Days Ago
In-Office
South San Francisco, CA, USA
200K-250K Annually
Entry level
200K-250K Annually
Entry level
Artificial Intelligence • Machine Learning • Robotics • Biotech
Train and deploy machine learning models for chemistry applications, including reaction planning, outcome prediction, material-cost estimation, and mass-spectra prediction. Responsibilities span data acquisition, model development, training infrastructure, parallelism, quantization, inference, and integration with robotic laboratory workflows. The role requires strong empirical machine learning fundamentals, cross-disciplinary collaboration, rapid experimentation, and comfort working across the full ML stack in an in-person chemistry lab environment.
Top Skills: Active LearningCheminformaticsComputer VisionData PipelinesDistributed TrainingEmbedded SystemsLarge Language ModelsMachine Learning FrameworksPyTorchQuantizationRobotics
14 Days Ago
In-Office
San Mateo, CA, USA
200K-400K Annually
Senior level
200K-400K Annually
Senior level
Professional Services • Consulting
Lead a research program focused on continual learning, model adaptation, self-improvement, and memory. Develop experiments, collaborate with ML and software engineers, and transition research into production features. The role requires applied research experience, post-training expertise for large models, strong Python and deep learning skills, distributed training experience, and publications at leading venues. This is an on-site senior individual contributor position in a fast-paced startup environment.
Top Skills: Deep Learning FrameworksLarge-Scale Multi-Machine TrainingMachine LearningPost-TrainingPythonReinforcement LearningSupervised Learning
29 Days Ago
In-Office or Remote
6 Locations
235K-270K Annually
Senior level
235K-270K Annually
Senior level
Artificial Intelligence • Biotech
Lead the design and deployment of large-scale bioinformatics and omics pipelines spanning genomics, transcriptomics, and proteomics. Integrate multimodal biological data with machine learning, develop reproducible analysis frameworks, benchmark predictive models, and collaborate with wet-lab scientists to guide molecular engineering and experimental campaigns. Contribute novel computational biology algorithms, research roadmaps, and scientific leadership.
Top Skills: DagsterGenomicsJaxMachine LearningNextflowProteomicsPythonPyTorchRSingle-Cell OmicsTranscriptomics

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account