Research Scientist, AI/ML Models ML, AI 🏆

Qualifications

• PhD in a scientific discipline or equivalent experience
• MS with over 6 years of relevant experience or BS with over 8 years of relevant experience
• Profound expertise in modern deep learning architectures including transformers, diffusion models, and generative models
• Strong experience in training large-scale models using PyTorch and distributed training frameworks
• Foundational knowledge in biology, chemistry, or disease biology to guide model development
• Experience with at least one of the following: protein language models, molecular generative models, or biomedical vision models
• Familiarity with cloud computing (AWS, GCP) and GPU cluster training at scale
• Knowledge of multimodal learning integrating text, images, and structured data
• Experience with omics data analysis and knowledge graphs
• Familiarity with protein structure prediction and 3D molecular representations
• Publications in top-tier ML venues or computational biology journals
• Experience in model compression and deployment of large models
• Strong background in data integration and multimodal modeling
• Proficiency in Python and ML libraries; familiarity with Unix tools
• Excellent collaboration and communication skills

Benefits

• Salary: $111 - 175,670 per year
• This position offers a hybrid work environment and competitive compensation, including eligibility for medical benefits, a 401(k) plan with company match, tuition reimbursement, and generous paid time off
• We are committed to fostering a diverse workforce and providing equitable pay and opportunities for all

Responsibilities

• Develop and train foundational AI models for drug discovery applications, capable of pre-training on large-scale scientific and molecular datasets
• Fine-tune pre-trained models for specific applications in target identification, disease modeling, and molecular design
• Construct multimodal models integrating diverse data types including omics, biomedical imaging, protein structures, and molecular representations
• Utilize advanced approaches including graph neural networks and transformer-based models
• Apply biological and chemical domain expertise to inform model architecture, data curation, and evaluation strategies
• Implement advanced generative architectures for molecular generation and optimization
• Collaborate with computational scientists to deploy models addressing various discovery needs across different platforms
• Remain updated on advancements in foundation models and contribute to knowledge sharing and publications

Full Description

Research Scientist, AI/ML Models 💰 Salary: $111 - 175,670 per year

At Takeda we are looking for a ML, AI engineer!

🛠️ Our tech stack:

3D, AI, AWS, Cloud, Flow, GCP, PyTorch, Python, TensorFlow, Unix, Machine-Learning

📝 Rquirements:

• PhD in a scientific discipline or equivalent experience

• MS with over 6 years of relevant experience or BS with over 8 years of relevant experience

• Profoundexpertise in modern deep learning architectures including transformers, diffusion models, and generative models

• Strong experience in training large-scale models using PyTorch and distributed training frameworks

• Foundational knowledge in biology, chemistry, or disease biology to guide model development

• Experience with at least one of the following: protein language models, molecular generative models, or biomedical vision models

• Familiarity with cloud computing (AWS, GCP) and GPU cluster training at scale

• Preferred experience in pharmaceutical or life sciences settings

• Knowledge of multimodal learning integrating text, images, and structured data

• Experience with omics data analysis and knowledge graphs

• Familiarity with protein structure prediction and 3D molecular representations

• Publications in top-tier ML venues or computational biology journals

• Experience in model compression and deployment of large models

• Strong background in data integration and multimodal modeling

• Proficiency in Python and ML libraries; familiarity with Unix tools

• Excellent collaboration and communication skills

👩‍💻👨‍💻 Your responsibilities are:

• Develop and train foundational AI models for drug discovery applications, capable of pre-training on large-scale scientific and molecular datasets

• Fine-tune pre-trained models for specific applications in target identification, disease modeling, and molecular design

• Construct multimodal models integrating diverse data types including omics, biomedical imaging, protein structures, and molecular representations

• Utilize advanced approaches including graph neural networks and transformer-based models

• Apply biological and chemical domain expertise to inform model architecture, data curation, and evaluation strategies

• Implement advanced generative architectures for molecular generation and optimization

• Collaborate with computational scientists to deploy models addressing various discovery needs across different platforms

• Remain updated on advancements in foundation models and contribute to knowledge sharing and publications

View this job and over 500 other transparent jobs with salaries (💰💰💰) & tech stacks (🛠️) on DevITJobs

Category: ML, AI Developer / Engineer

Location address: Kendall Street 500, Boston, United States

Salary: $111 - 175,670 per year

Benefits & perks that we offer:

Takeda - More about us and the role:

At Takeda, we are on the forefront of revolutionizing drug discovery through cutting-edge AI technologies.

We are looking for dedicated Scientists to join our AI/ML Foundation team in Cambridge, MA, working on foundational models that integrate diverse data types.

This position offers a hybrid work environment and competitive compensation, including eligibility for medical benefits, a 401(k) plan with company match, tuition reimbursement, and generous paid time off.

We are committed to fostering a diverse workforce and providing equitable pay and opportunities for all.

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