Full-Time

Senior Machine Learning Engineer

Machine Learning

Updated on 9/4/2026

Dyno Therapeutics

Dyno Therapeutics

51-200 employees

AI-designed AAV vectors for gene therapy

Compensation Overview

$178.7k - $213.7k/yr

+ Annual performance-based bonus + Stock options

Watertown, MA, USA

Remote

Category
AI & Machine Learning (1)
Required Skills
LLM
Kubernetes
MLOps
Software Testing
CUDA
Machine Learning
Docker
Version Control

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Requirements
  • At least 5 years of professional experience building software for machine learning.
  • Strong software engineering fundamentals, including object-oriented design, testing, version control, dependency management, and application programming interface design.
  • Experience containerizing code for remote environments, including hands-on experience with Docker and Kubernetes.
  • Experience with large-scale distributed training or inference using Ray or a similar framework.
  • Familiarity with machine learning performance engineering, including identifying bottlenecks, analyzing resource usage, profiling, and writing custom kernels.
  • Experience designing and owning technically complex systems through requirements-setting, implementation, rollout, and maintenance.
  • Ability to contribute to technical direction through design reviews, cross-team planning, and documentation.
  • Ability to find solutions proactively when challenges arise.
Responsibilities
  • Build modular, generalizable, and portable machine learning training systems that support the ongoing development of protein design models.
  • Improve the scalability, reliability, and performance of machine learning training and inference infrastructure to enable rapid research experimentation.
  • Optimize model performance using GPU profiling, custom kernels, and modern accelerated computing frameworks.
  • Develop and standardize agentic artificial intelligence workflows that increase research velocity while maintaining appropriate safety and reliability.
  • Partner with AI scientists, protein engineers, and other machine learning engineers to translate research prototypes into robust, reusable tools and systems.
  • Contribute across the machine learning engineering stack, including modeling, GPU-level optimization, distributed training, and multi-node orchestration.
  • Stay current on emerging machine learning engineering and agentic artificial intelligence tools and help the team evaluate and adopt approaches that advance research.
  • Support the delivery and communication of the company's work internally and externally.
  • Design and own technically complex systems through requirements-setting, implementation, rollout, and maintenance.
  • Contribute to technical direction through design reviews, cross-team planning, and documentation.
  • Collaborate cross-functionally to drive results.
Desired Qualifications
  • Professional or academic experience in machine learning research or scientific computing.
  • Experience building internal platforms or developer tools.
  • Familiarity with common MLOps tools and practices, including model monitoring, model versioning, continuous integration and continuous delivery, and model registries.
  • Experience with GPU programming, including CUDA or Triton.
  • High proficiency in agentic artificial intelligence and modern AI tools for software development.
  • Exposure to biology, bioinformatics, structural biology, or protein modeling.

Dyno Therapeutics designs optimized AAV vectors for gene therapy using AI. Its platform creates tailored AAV vectors to improve delivery and effectiveness of genetic medicines. The company collaborates with pharmaceutical and biotech partners such as Astellas, Roche, Sarepta, and Novartis to advance therapies targeting skeletal and cardiac muscles, the central nervous system, liver, and eyes. Revenue comes from partnerships in which Dyno provides vector designs and optimization services for R&D. Unlike purely in-house biotechs, Dyno emphasizes AI-driven vector design and active collaborations with major pharma players to speed development. The company’s goal is to help bring safer and more effective gene therapies to patients by expanding the range and performance of AAV delivery systems.

Company Size

51-200

Company Stage

Series A

Total Funding

$109M

Headquarters

Watertown, Massachusetts

Founded

2018

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Simplify Jobs

Simplify's Take

What believers are saying

  • Dyno launched Dyno-9zh and Dyno-n96 at ASGCT 2026, widening CNS and muscle coverage.
  • Frontiers added Trisk Bio in November 2025, reducing manufacturing friction for partner programs.
  • Dyno Psi-Phi and open-weight Psi-1 deepen platform reach beyond capsids into protein design.

What critics are saying

  • Astellas and Roche validate delivery, not full drug pipelines, so Dyno still lacks durable product revenue.
  • Headcount fell to 90 employees by March 2026, and Dyno posted zero jobs.
  • AAV competition from 4DMT, Voyager, and Beacon can commoditize capsid discovery by 2027.

What makes Dyno Therapeutics unique

  • Dyno's CapsidMap platform turns NHP data into tissue-targeted AAV designs across species.
  • Astellas paid $15 million in April 2026 for Dyno's first licensed muscle capsid.
  • Dyno's Frontiers Network spans 15 developers, seven manufacturers, six services, and 15 investors.

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Benefits

Remote Work Options

Growth & Insights and Company News

Headcount

6 month growth

-2%

1 year growth

-4%

2 year growth

-5%
Genetic Engineering & Biotechnology News
Jun 23rd, 2026
Nvidia unveils science reasoning AI suite with BioNeMo Agent Toolkit.

Nvidia unveils science reasoning AI suite with BioNeMo Agent Toolkit. June 23, 2026 Nvidia has announced the NVIDIA BioNeMo Agent Toolkit, which turns complex scientific workflows into agent-executable tasks, including model selection, input preparation, workflow execution, output inspection, and results explanation. The toolkit includes NVIDIA BioNeMo and is powered by NVIDIA NIM microservices, NVIDIA Parabricks, NVIDIA NeMo, and NVIDIA Nemotron and has applications across protein structure prediction, molecular docking, generative chemistry, genomic analysis, protein design, and biomarker discovery. "For the first time, researchers can build AI agents that understand scientific knowledge, use scientific tools, and execute scientific workflows," said Jensen Huang, founder and CEO of Nvidia, in a press release. "This is a new way to do science - one that can dramatically accelerate discovery across biology, chemistry, genomics, and medicine." Nvidia has entered collaborations with research organizations, including the Arc Institute, Open Molecular Software Foundation, and the University of Washington's Institute for Protein Design (IPD). The partnership with IPD has accelerated runtimes for the biomolecular complex prediction tool, RosettaFold3, resulting in two times faster performance than the prior generation model. "Every tool we've built for protein design is only as powerful as the scientists who can efficiently access it," said David Baker, PhD, professor of biochemistry at the University of Washington and director of the Institute for Protein Design, in a public release. "The next leap in science won't come from a single discovery; it will come from the speed of iterative designs and agents that can repeatedly reason through the complexity of biology at a speed humans never could." The toolkit's applications include virtual screening, where agents identify promising small-molecule drug candidates by generating compound designs, docking them to a target, predicting binding strength, and filtering for developability properties. The agent can then output which candidates should be prioritized to compress timelines. In genomic analysis and target discovery, agents can identify genetic insights and biological targets from raw sequencing data. Agents can also connect real-world data to reasoning models for biomedical research, improving the efficiency and accuracy of clinical development processes, including literature review, protocol generation, clinical trial screening, and pharmacovigilance. In medical imaging analysis, agents can process, segment, synthesize, and reason over medical imaging data to support biomarker discovery. AI-native biology companies, including Boltz, Basecamp Research, Chai Discovery, PerturbAI, Dyno, and Proxima, have collaborated with NVIDIA to develop tools to accelerate therapeutic design workflows. Diagnostics and pharmaceutical companies, including Lilly and Natera, are using BioNeMo Agent Toolkit to scale agentic workflows across discovery, translational research, and clinical insight.

BizWorld Ireland
May 15th, 2026
Dyno Therapeutics expands Frontiers Network and announces second annual GATC conference.

Dyno Therapeutics expands Frontiers Network and announces second annual GATC conference. May 15, 2026 By jan Dyno Therapeutics has unveiled substantial expansion plans for its Frontiers Network collaborative research initiative while simultaneously announcing the second annual Genetic Agency Technology Conference (GATC), signaling accelerated momentum in artificial intelligence-driven gene therapy development. The biotechnology company's dual announcements position it as a central hub for advancing next-generation adeno-associated virus (AAV) capsid engineering through strategic industry partnerships. The Frontiers Network expansion represents a strategic effort to broaden the application of Dyno's proprietary CapsidMap platform, which utilizes machine learning algorithms to design optimized viral vectors for gene therapy delivery. This collaborative framework enables pharmaceutical companies, academic institutions, and research organizations to leverage Dyno's computational biology capabilities for developing targeted therapeutic solutions. The network's growth trajectory reflects increasing industry recognition of AI-enhanced drug development methodologies, particularly in overcoming traditional gene therapy delivery challenges such as tissue specificity and immune response mitigation. Established as a partnership-driven initiative, the Frontiers Network facilitates access to Dyno's extensive capsid sequence database and predictive modeling tools. Member organizations gain capabilities to accelerate their gene therapy programs by identifying optimal AAV variants for specific therapeutic applications. The expansion arrives as the global gene therapy market continues rapid growth, with industry analysts projecting the sector to reach approximately $30 billion by 2030, driven by increasing regulatory approvals and expanding clinical applications across rare genetic disorders, oncology, and central nervous system conditions. The second annual GATC conference will serve as a convergence point for gene therapy researchers, biotechnology executives, and computational biologists to examine emerging developments in capsid engineering and vector optimization. This gathering follows the inaugural conference's success in establishing dialogue between traditional virology researchers and artificial intelligence practitioners working to transform therapeutic delivery mechanisms. Conference programming will emphasize translational research outcomes, regulatory pathway considerations, and manufacturing scalability challenges that currently constrain broader gene therapy adoption. Dyno Therapeutics operates at the intersection of synthetic biology and machine learning, applying computational design principles to historically empirical capsid development processes. The company's approach addresses fundamental limitations in natural AAV serotypes, which often exhibit suboptimal tissue tropism or trigger unwanted immune responses when deployed as therapeutic vectors. By generating and analyzing vast datasets of capsid variants, Dyno's platform identifies sequence-function relationships that would remain obscure through conventional experimental methods alone. The biotechnology company has established multiple strategic collaborations with major pharmaceutical organizations seeking to enhance their gene therapy pipelines. These partnerships typically provide Dyno with financial support and clinical development expertise while granting partners access to novel capsid designs tailored for specific therapeutic indications. This business model leverages the company's computational infrastructure across multiple therapeutic programs simultaneously, creating operational efficiencies compared to traditional single-asset biotechnology development approaches. Gene therapy delivery optimization remains a critical bottleneck in translating promising genetic medicines from laboratory research to clinical practice. Existing AAV serotypes demonstrate variable transduction efficiency across different tissue types, necessitating either higher vector doses that increase manufacturing costs and safety concerns, or acceptance of suboptimal therapeutic efficacy. Dyno's machine learning methodology systematically explores capsid sequence space to identify variants with enhanced performance characteristics, potentially reducing dosing requirements and improving therapeutic windows. The GATC conference agenda will address manufacturing considerations that increasingly influence gene therapy commercialization prospects. Production scalability challenges and quality control requirements significantly impact the economic viability of genetic medicines, particularly for rare disease applications serving limited patient populations. Industry experts anticipate that AI-designed capsids offering improved manufacturing characteristics could substantially reduce production costs while maintaining therapeutic performance standards established by regulatory agencies including the U.S. Food and Drug Administration. As the Frontiers Network expands and the annual conference establishes itself as a premier gene therapy technology forum, Dyno Therapeutics positions itself as an essential infrastructure provider for the emerging computational biology ecosystem. The company's evolution reflects broader pharmaceutical industry trends toward platform-based partnership models that distribute development risks while accelerating innovation timelines across multiple therapeutic areas simultaneously.

Business Wire
May 13th, 2026
Dyno Therapeutics unveils AI-designed AAV capsids for CNS and muscle gene delivery at ASGCT 2026

Dyno Therapeutics has launched two new adeno-associated virus capsids for gene delivery at the American Society of Gene & Cell Therapy Annual Meeting. The company unveiled Dyno-9zh for central nervous system delivery and Dyno-n96 for muscle delivery, alongside updated results for previously released capsids. The AI-powered platform, trained on billions of non-human primate measurements, engineers capsids optimized for selective delivery and cross-species translatability. Dyno-9zh demonstrates exceptional performance across species, achieving up to 50% neuronal transduction in primate brains at lower liver biodistribution than AAV9. Dyno-n96 delivers efficient muscle transduction at approximately 25-fold lower doses than existing therapies. The company also introduced Dyno Psi-1, an AI foundation model for protein binder design, and Dyno Phi, an agentic platform for therapeutic development now available to rare disease communities.

Business Wire
Apr 8th, 2026
Astellas exercises capsid license from Dyno Therapeutics for $15M, validating AI-designed gene delivery

Dyno Therapeutics announced that Astellas Pharma has exercised its option to licence a novel adeno-associated virus capsid engineered for therapeutic delivery to skeletal muscle. This marks Dyno's first licensed muscle capsid and its second capsid licence overall, following Roche's exercise of an option for a neurological disease capsid in January 2025. The AI-designed capsid demonstrates superior skeletal muscle targeting in non-human primates whilst leveraging existing AAV9-based manufacturing processes. Traditional gene therapies for muscle disorders have faced challenges with wild-type AAV capsids requiring high doses, creating safety risks and significant manufacturing costs. Under the 2021 collaboration agreement, Astellas will pay Dyno a $15 million licence fee. Dyno is eligible to receive clinical development, regulatory and commercial milestone payments, plus royalties on resulting products.

BioPharmaTrend
Mar 18th, 2026
Dyno launches open-source agentic protein design suite at GTC 2026.

Dyno launches open-source agentic protein design suite at GTC 2026.