Full-Time

Machine Learning Scientist

Large Multimodal Models, Post-Training

Iambic Therapeutics

Iambic Therapeutics

51-200 employees

AI-driven discovery for oncology and neurology

No salary listed

Boston, MA, USA

Hybrid

Remote position with an option to work on-site in the Boston office.

PhD

Category
AI & Machine Learning (1)
Required Skills
LLM
Kubernetes
Python
High Performance Computing (HPC)
Neural Networks
CUDA
PyTorch
Machine Learning
Medicinal Chemistry
Docker
Reinforcement Learning

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Requirements
  • A PhD in machine learning, computer science, computational chemistry, physics, or a related computational STEM field, or equivalent industry experience demonstrating comparable depth.
  • Strong Python and PyTorch skills, including implementing, training, debugging, and evaluating deep learning models end-to-end.
  • Demonstrated experience training large-scale transformer models.
  • Experience with reinforcement learning approaches such as RLHF, RLAIF, PPO, GRPO, reinforcement learning with verifiable rewards, or related methods.
  • Experience with supervised fine-tuning, full-parameter fine-tuning, parameter-efficient fine-tuning such as LoRA, or related methods.
  • Experience with systematic hyperparameter optimization or large-scale experimentation using tools such as Optuna, Ray Tune, or similar frameworks.
  • Strong engineering practices, including reproducible experimentation, clean code, testing, and performance-aware debugging.
  • Comfort with modern machine learning infrastructure such as Docker, CUDA, Kubernetes, and experiment tracking tools such as Weights & Biases.
Responsibilities
  • Research and develop post-training strategies for large-scale multimodal foundation models.
  • Design reward functions, training objectives, data-generation strategies, and evaluation protocols for reinforcement learning and other post-training approaches applied to multimodal large language models.
  • Build systematic experimentation and hyperparameter optimization workflows to efficiently explore post-training recipes, model configurations, and training strategies.
  • Develop and apply inference optimization techniques to support deployment in high-throughput model evaluation and interactive discovery workflows.
  • Design and maintain rigorous benchmarking and evaluation frameworks that measure model quality across modalities, downstream tasks, and scientific use cases.
  • Collaborate with machine learning and software engineering colleagues to productionize models, evaluation systems, and inference services.
  • Partner with computational chemists, medicinal chemists, and biologists to ensure model development and post-training objectives are grounded in drug discovery needs.
  • Communicate results to internal teams, external partners, and at conferences.
  • Write high-quality research and engineering code by refactoring, testing, documenting, and packaging machine learning components to support team velocity.
Desired Qualifications
  • Experience with multimodal or multi-task model architectures.
  • Training and inference optimization, including mixed precision, kernel optimization, quantization, and distributed strategies.
  • Familiarity with biomedical, chemical, or biological data domains.
  • Distributed training at scale.
  • HPC or large-scale training operations experience.

Iambic Therapeutics develops therapeutics using an AI-driven discovery platform, focusing on oncology and neurological diseases in clinical-stage programs. The platform combines advanced AI models with automated experiments to predict molecular properties faster and with less data, speeding identification and optimization of drug candidates. It differentiates itself by maintaining an in-house pipeline alongside strategic pharmaceutical partnerships to advance programs and earn milestones and royalties. The goal is to bring new therapies to patients by accelerating discovery and development through AI and automation.

Company Size

51-200

Company Stage

Late Stage VC

Total Funding

$303M

Headquarters

San Diego, California

Founded

2019

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Simplify Jobs

Simplify's Take

What believers are saying

  • Takeda’s February 2026 deal provides upfront, research, and technology-access payments.
  • Bayer joined June 2026, expanding non-dilutive validation beyond oncology into broader drug discovery.
  • Iambic raised over $100 million in November 2025, supporting runway into 2028.

What critics are saying

  • Takeda’s billion-dollar value depends on milestones; failure in programs kills economics.
  • IAM1363 remains single-asset clinical proof; Phase 1b setbacks would crush credibility.
  • Big pharma can internalize AI discovery, and Bayer or Takeda can switch vendors.

What makes Iambic Therapeutics unique

  • NeuralPLexer and Enchant anchor Iambic’s AI stack for structure and endpoint prediction.
  • Takeda chose Iambic in February 2026, validating platform value with blue-chip pharma.
  • IAM1363 reached Phase 1/1b in two years, versus six-year industry averages.

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Benefits

Health Insurance

401(k) Company Match

Unlimited Paid Time Off

Growth & Insights and Company News

Headcount

6 month growth

0%

1 year growth

0%

2 year growth

-2%
Intelligence360 News
Dec 3rd, 2025
Iambic Therapeutics raises $125M in new funding

Iambic Therapeutics has filed a notice with the US Securities and Exchange Commission for an exempt offering to raise $125 million in new funding. The filing was made under Rule 504 or 506 of Regulation D or Section 4(a)(5) of the Securities Act, which allows companies to sell securities without registration under the Securities Act of 1933. Federal securities law requires such notices to be filed within 15 days after the first sale of securities in the offering. No additional details about the funding round, including investors or valuation, were disclosed in the filing.

Iambic Therapeutics
Nov 11th, 2025
Iambic Raises Over $100 Million in an Oversubscribed Round to Advance its Portfolio of AI-Discovered Therapeutics and Leading Platform Technologies

San Diego, CA – Nov. 10, 2025 – Iambic, a clinical-stage life science and technology company developing novel medicines using its AI-driven discovery and development platform, today announced raising over $100 million in an oversubscribed financing round with balanced support from new and existing investors, including Abingworth, Alexandria Venture Investments, Alumni Ventures, ARK, Ascenta, Catalio, Everbright Biofund, Freeflow Ventures, Illumina Ventures, Mubadala, Pegasus Tech Ventures, Qatar Investment Authority, Regeneron Ventures, Sequoia, Tao Capital Partners, Terra Magnum Capital Partners, Wilson Sonsini Goodrich & Rosati, and others.

Endpoints News
Nov 10th, 2025
Iambic Therapeutics raises $100M funding

Iambic Therapeutics has secured over $100 million in a new funding round, as revealed by CEO Tom Miller. The investment comes from ARK and Regeneron, highlighting significant financial backing for the San Diego-based biotech company.

EntArabi
Jun 20th, 2024
Iambic Therapeutics raises $50M in Series B

Iambic Therapeutics, a US-based biotech company, raised $50 million in an expanded Series B funding round led by Mubadala Capital. The round included Qatar Investment Authority, Exor Ventures, and existing investors like Abingworth, Illumina Ventures, Nexus Venture Partners, Coatue, and Tao Capital Partners. This funding is part of a previous $100 million Series B round closed in October 2023. The funds will be used to advance Iambic's clinical and preclinical programs.

Pharmaceutical Business Review
Jun 19th, 2024
Iambic secures $50m to bolster clinical oncology programme pipeline

Iambic Therapeutics has secured $50m in its Series B extension financing round to bolster its pipeline comprising clinical oncology programmes.