Research Engineer / Scientist – Modeling

About the role

As a Research Engineer/Scientist (LLM Modeling) at Percepta, you will advance the frontier of large-scale language model building and deployment. You will work on pre-training, post-training (e.g., instruction tuning, alignment, distillation), reinforcement learning (RL), and the design of specialized architectures to push the boundaries of reasoning, decision-making, and adaptability in critical industries.

You will collaborate closely with our Embedded Product Managers (EPMs) and engineers to ensure our most sophisticated decision systems are both innovative and pragmatically useful in transforming how companies operate.

Responsibilities

• Identify impactful problems and design research strategies across pre-training, post-training, RL, and specialized model development.
• Prototype and scale training pipelines for large language models, experiment with model architectures, optimization techniques, and post-training strategies.
• Contribute to infrastructure for high-performance distributed training.
• Conduct in-the-wild evaluations at scale that drive millions of dollars in value.
• Partner with our applied AI engineers to transition successful research ideas into robust features of our Mosaic platform.
• Communicate research outcomes to both technical and non-technical stakeholders, making sure everyone understands the “so what” of research and how to apply it.

Requirements

• Have an MS/PhD in Computer Science, ML, a related field, or equivalent experience.
• Have depth in LLM and ML fundamentals from optimization to large scale training to Reinforcement Learning.
• Be comfortable implementing and debugging large-scale ML systems.
• Be motivated by impact in critical industries including healthcare, supply chains, energy, and finance.
• Have a proven track record of execution.
• Be an excellent communicator with both technical and non-technical stakeholders.
• Enjoy extreme ownership.
• Be passionate about AI’s transformative potential.

Qualifications

• MS/PhD in Computer Science, ML, a related field, or equivalent experience.
• Depth in LLM and ML fundamentals from optimization to large scale training to Reinforcement Learning.
• Comfortable implementing and debugging large-scale ML systems.
• Motivated by impact in critical industries including healthcare, supply chains, energy, and finance.
• Proven track record of execution.
• Excellent communicator with both technical and non-technical stakeholders.
• Extreme ownership.
• Passionate about AI’s transformative potential.

Skills

• Strong programming skills in Python, C++, or other relevant languages.
• Experience with large-scale machine learning frameworks such as TensorFlow, PyTorch, or Hugging Face Transformers.
• Knowledge of natural language processing (NLP) and deep learning techniques.
• Experience with reinforcement learning and/or transfer learning.
• Ability to work independently and collaboratively in a fast-paced environment.

Benefits

• Competitive salary commensurate with experience.
• Flexible work schedule.
• Health insurance and retirement plans.
• Professional development opportunities.
• Work-life balance with minimal monitoring of hours.

Pay

Competitive salary commensurate with experience.

Schedule

Flexible work schedule.

Benefits

• Health insurance and retirement plans.
• Professional development opportunities.
• Work-life balance with minimal monitoring of hours.