Develop advanced machine learning solutions for content understanding across audio, text, and multimodal sources.
Responsibilities
Design, develop, deploy, and improve machine learning models that support content understanding across audio, text, and multimodal content sources.
Apply modern machine learning techniques, including deep learning, transformer architectures, large language models, and multimodal learning approaches to solve content understanding challenges.
Own complex machine learning projects from problem definition through model development, deployment, evaluation, and ongoing optimization.
Evaluate model performance using appropriate offline metrics, experimentation frameworks, and business outcomes to drive continuous improvement.
Collaborate closely with Product, Engineering, Analytics, and Data teams to identify opportunities and deliver impactful machine learning solutions.
Forward Deployed Engineer responsible for translating customer needs into research and engineering solutions, building prototypes, and deploying Odyssey’s world models in real-world environments.
Responsibilities
Embed closely with strategic customers to understand workflows and constraints
Identify opportunities for world models across robotics, simulation, autonomy, training, interactive media, and other domains
Translate customer goals into research and engineering problems, prototypes, and deployment plans
Adapt and extend Odyssey’s models through fine‑tuning, post‑training, conditioning, controllability, inference optimization, and learned control policies
Build end‑to‑end prototypes connecting models to customer data, tools, simulators, hardware, and production systems
Apply state‑of‑the‑art deep learning techniques to search, curate, and evaluate high‑quality datasets and ground truth for autonomous vehicles.
Compensation
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are: 152,000 USD – 241,500 USD for Level 3; and 184,000 USD – 287,500 USD for Level 4.
Responsibilities
Stay up to date with the latest research and innovations in deep learning, implement and experiment with new ideas.
Foster collaborative partnerships with researchers and engineers, transforming innovative research into robust, industrial‑strength machine learning models.
Take approaches from initial evaluation and experimentation all the way to shipping.
Define, collect, and curate training and evaluation datasets, focusing on scenario coverage and label quality.
Develop vision‑language models and embeddings for scenario search, classification, and automated data curation.
Requirements
PhD in Computer Science
MS in Computer Science
Nice to have: background applying latest AI methods to solve computer vision and autonomous vehicle problems
Nice to have: experience with vision‑language models
Apply state‑of‑the‑art deep learning and computer vision techniques to curate high‑quality datasets and ground truth for autonomous vehicle perception, prediction, planning and control.
Compensation
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are: 152,000 USD – 241,500 USD for Level 3; and 184,000 USD – 287,500 USD for Level 4.
Responsibilities
Stay up to date with the latest research and innovations in deep learning, implement and experiment with new ideas.
Foster collaborative partnerships with researchers and engineers, transforming innovative research into robust, industrial‑strength machine learning models.
Take approaches from initial evaluation and experimentation all the way to shipping.
Define, collect, and curate training and evaluation datasets, focusing on scenario coverage and label quality.
Develop vision‑language models and embeddings for scenario search, classification, and automated data curation.
Requirements
PhD in Computer Science, Computer Engineering, or related field
MS in Computer Science, Computer Engineering, or related field
Develop and advance machine learning methods that learn from and reason across complex biomedical, clinical, molecular, and scientific data for drug discovery and development.
Compensation
The annual base salary for this position ranges from $139,100.00 to $231,900.00. In addition, this position is eligible for participation in Pfizer’s Global Performance Plan with a bonus target of 17.5% of the base salary and eligibility to participate in our share based long term incentive program.
Responsibilities
Develop Frontier AI Methods for Biomedical Research: Create, adapt, and improve foundation models, multimodal and graph-based approaches, generative methods, and agentic reasoning systems.
Design and Execute Rigorous Experiments: Form clear hypotheses and design controlled, reproducible experiments.
Set the Evaluation Standard At Scale: Design the datasets, benchmarks, and validation strategies that show whether a model can be trusted.
Translate models into scientific evidence: Work with AI engineers, computational biologists, and domain experts to test hypotheses and interpret results, uncertainty, and limitations.
Build the shared foundation: Develop reusable methods, benchmarks, model components, and workflows, and work with engineering to run them on common infrastructure.
Requirements
PhD in Machine Learning, Artificial Intelligence, Computer Science, Statistics, Applied Mathematics, Computational Biology, or a related quantitative field
Master's degree
Nice to have: 5+ years of relevant relevant industry or research experience
Develop and advance machine learning methods that learn from and reason across complex biomedical, clinical, molecular, and scientific data.
Compensation
The annual base salary for this position ranges from $106,000.00 to $176,600.00. In addition, this position is eligible for participation in Pfizer’s Global Performance Plan with a bonus target of 15.0% of the base salary and eligibility to participate in our share based long term incentive program.
Responsibilities
Develop frontier AI methods for biomedical research
Design and execute rigorous experiments
Set the evaluation standard at scale
Translate models into scientific evidence
Build shared foundation
Requirements
PhD in Machine Learning, Artificial Intelligence, Computer Science, Statistics, Applied Mathematics, Computational Biology or related quantitative field
Master's degree with 2+ years of relevant industry or research experience
Nice to have: Experience applying AI in life sciences, biotechnology, healthcare, pharmaceuticals, or biomedical research
Nice to have: Experience with biological, molecular, imaging, clinical, or real-world health data
Nice to have: Experience building foundation models or multimodal learning systems for scientific applications
Lead advanced AI research to accelerate drug discovery and development at Pfizer.
Compensation
The annual base salary for this position ranges from $139,100.00 to $231,900.00. In addition, this position is eligible for participation in Pfizer’s Global Performance Plan with a bonus target of 17.5% of the base salary and eligibility to participate in our share based long term incentive program.
Responsibilities
Develop frontier AI methods for biomedical research
Design and execute rigorous experiments
Set evaluation standards at scale
Translate models into scientific evidence
Build shared foundations
Requirements
PhD in Machine Learning, Artificial Intelligence, Computer Science, Statistics, Applied Mathematics, Computational Biology or related field
Master's degree with 5+ years of relevant industry or research experience
Nice to have: Experience applying AI in life sciences, biotechnology, healthcare, pharmaceuticals, or biomedical research
Nice to have: Experience with biological, molecular, imaging, clinical, or real-world health data
Nice to have: Experience building foundation models or multimodal learning systems for scientific applications
Develop and advance machine learning methods that learn from and reason across complex biomedical, clinical, molecular, and scientific data.
Compensation
The annual base salary for this position ranges from $106,000.00 to $176,600.00. In addition, this position is eligible for participation in Pfizer’s Global Performance Plan with a bonus target of 15.0% of the base salary and eligibility to participate in our share based long term incentive program.
Responsibilities
Develop frontier AI methods for biomedical research
Design and execute rigorous experiments
Set the evaluation standard at scale
Translate models into scientific evidence
Build the shared foundation
Requirements
PhD in Machine Learning, Artificial Intelligence, Computer Science, Statistics, Applied Mathematics, Computational Biology or related quantitative field
Master's degree with 2+ years of relevant industry or research experience
Nice to have: Experience applying AI in life sciences, biotechnology, healthcare, pharmaceuticals, or biomedical research
Nice to have: Experience with biological, molecular, imaging, clinical, or real-world health data
Nice to have: Experience building foundation models or multimodal learning systems for scientific applications
Lead the development of AI/ML methods for biologics design, integrating protein science and drug discovery to accelerate therapeutic candidate optimization.
Compensation
The salary range for this position is: $169,320.00 - $219,120.00. Gilead considers a variety of factors when determining base compensation, including experience, qualifications, and geographic location. These considerations mean actual compensation will vary. This position may also be eligible for a discretionary annual bonus, discretionary stock-based long-term incentives (eligibility may vary based on role), paid time off, and a benefits package.
Responsibilities
Develop novel machine learning approaches to support biologics discovery and lead optimization.
Apply and extend protein language models, foundation models, and representation learning methods for therapeutic protein design.
Build predictive models linking sequence, structure, and experimental measurements to key molecular properties.
Develop structure-aware learning approaches that incorporate protein conformation, interfaces, and molecular context.
Design and evaluate generative methods for exploring protein sequence space and proposing improved therapeutic candidates.
Requirements
Ph.D. in Computational Biology, Machine Learning, Computer Science, Structural Biology, Biophysics, Bioengineering, or a related quantitative field
Nice to have: protein language models and foundation models for proteins or antibodies
Senior Machine Learning Scientist, Content UnderstandingNewSiriusXM · Dublin, Ireland
Member of Technical Staff, Forward Deployed EngineerOdyssey · Palo Alto, US