Breakout Ventures
Member of the Technical Staff - AI/ML Scientist
Breakout Ventures, Cambridge, Massachusetts, us, 02140
Member of the Technical Staff – AI/ML Scientist
We’re leveraging AI to solve one of the most consequential challenges in the pursuit of technical progress: the distribution of scientific innovations to the real world. We’re well‑funded with top investors and are building a world class team.
Work With Us Your impact starts here. We enthusiastically invite applicants across a broad range of expertise and experience to apply. Each candidate that joins the team will be a member of the technical staff, and compensation will depend on experience and responsibility. We work across AI and biotech innovation, so even if you apply for one role, we may consider you for others as well. We’re based in Cambridge, MA, but invite applications from all geographies.
What You Can Expect From Us
Opportunity to join a creative and mission‑oriented founding team and build with us from the ground up
Bias for action and obsession with solving our customers’ real problems
Love for bold, audacious science, enabling moonshots, and a motivation to work with and across the entire ecosystem
Full HR compensation stack to include competitive salary, equity, and benefits
What You’ll Accomplish With Us
Design and implement novel machine learning approaches—especially in pre‑training, multimodal learning, and reinforcement learning—to make experimental science more reproducible, interpretable, and transferable at scale.
Design and develop AI models that can learn from experimental protocols, lab execution data, and failure modes to suggest, simulate, or guide future experiments.
Develop and implement data collection strategies—including computer vision, audio, and sensor‑driven interfaces—to capture tacit knowledge embedded in physical lab workflows and human decision‑making.
Become customer obsessed: initiate, support, and lead program execution with external partners and collaborators to capture, document, and deliver results.
Develop and test internal and external benchmarks, validation strategies, and frameworks for testing reproducibility, robustness, and scientific utility.
Work alongside the biology and operations teams to identify automation opportunities, uncover latent structures in messy lab data, capture tacit knowledge, and improve experiment documentation and reproducibility.
Translate scientific hypotheses into computational experiments, analyzing model behavior and experimental results to draw actionable insights.
Stay on top of the latest research in ML/AI and evaluate its applicability to our platform. Supporting opportunities to publish or present where appropriate to establish technical leadership.
Requirements
Advanced degree in Computer Science, Machine Learning, or a related field.
Deep expertise in generative models, representation learning, multimodal learning, reinforcement learning, and/or causal inference.
Fluency in Python, modern ML libraries (e.g., PyTorch), and cloud infrastructure (e.g., AWS, GCP).
Demonstrated ability to design and implement ML models in noisy, complex, real‑world settings—ideally involving biological or scientific data.
Additional Preferences
Experience in a scientific or research‑intensive environment—academic labs, biotech R&D, national labs, or similar.
Familiarity with experimental workflows, lab automation, or scientific instrumentation.
Startup or early‑stage experience preferred; comfort with ambiguity and rapid iteration is a must.
Ability to clearly communicate technical concepts to cross‑functional teams and collaborate on projects spanning AI, biology, and product.
Ideal candidates are located within commuting distance from Cambridge, MA.
Apply now
#J-18808-Ljbffr
Work With Us Your impact starts here. We enthusiastically invite applicants across a broad range of expertise and experience to apply. Each candidate that joins the team will be a member of the technical staff, and compensation will depend on experience and responsibility. We work across AI and biotech innovation, so even if you apply for one role, we may consider you for others as well. We’re based in Cambridge, MA, but invite applications from all geographies.
What You Can Expect From Us
Opportunity to join a creative and mission‑oriented founding team and build with us from the ground up
Bias for action and obsession with solving our customers’ real problems
Love for bold, audacious science, enabling moonshots, and a motivation to work with and across the entire ecosystem
Full HR compensation stack to include competitive salary, equity, and benefits
What You’ll Accomplish With Us
Design and implement novel machine learning approaches—especially in pre‑training, multimodal learning, and reinforcement learning—to make experimental science more reproducible, interpretable, and transferable at scale.
Design and develop AI models that can learn from experimental protocols, lab execution data, and failure modes to suggest, simulate, or guide future experiments.
Develop and implement data collection strategies—including computer vision, audio, and sensor‑driven interfaces—to capture tacit knowledge embedded in physical lab workflows and human decision‑making.
Become customer obsessed: initiate, support, and lead program execution with external partners and collaborators to capture, document, and deliver results.
Develop and test internal and external benchmarks, validation strategies, and frameworks for testing reproducibility, robustness, and scientific utility.
Work alongside the biology and operations teams to identify automation opportunities, uncover latent structures in messy lab data, capture tacit knowledge, and improve experiment documentation and reproducibility.
Translate scientific hypotheses into computational experiments, analyzing model behavior and experimental results to draw actionable insights.
Stay on top of the latest research in ML/AI and evaluate its applicability to our platform. Supporting opportunities to publish or present where appropriate to establish technical leadership.
Requirements
Advanced degree in Computer Science, Machine Learning, or a related field.
Deep expertise in generative models, representation learning, multimodal learning, reinforcement learning, and/or causal inference.
Fluency in Python, modern ML libraries (e.g., PyTorch), and cloud infrastructure (e.g., AWS, GCP).
Demonstrated ability to design and implement ML models in noisy, complex, real‑world settings—ideally involving biological or scientific data.
Additional Preferences
Experience in a scientific or research‑intensive environment—academic labs, biotech R&D, national labs, or similar.
Familiarity with experimental workflows, lab automation, or scientific instrumentation.
Startup or early‑stage experience preferred; comfort with ambiguity and rapid iteration is a must.
Ability to clearly communicate technical concepts to cross‑functional teams and collaborate on projects spanning AI, biology, and product.
Ideal candidates are located within commuting distance from Cambridge, MA.
Apply now
#J-18808-Ljbffr